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Pipeline run

67f0e487-75be-4e75-8669-b0e788dfe236

Pipeline LLM cost (USD)
API 1: $0.0089 API 2: $0.0002 API 3: $0.0000 Total: $0.0091

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · Data/ML Infrastructure
Build and operate large-scale Python data/ML infrastructure in cloud and containers: design architecture, integrate data from SQL/NoSQL/Hive/Hadoop/Snowflake, and work with Kubernetes, AWS, Docker, and MLOps tooling like SageMaker or MLflow.
"designing and building large-scale software and/or data architecture"
Tech stack maturity
Modern Cloud Native
The combination of AWS, Docker, Kubernetes, Python, SQL, and NoSQL is most indicative of a cloud-native, modern ML engineering stack.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
2.00 / 5
Title match
Has AI skill
· AI skill (primary)
AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3): MLOps, Machine Learning
Evidence — skills matched in JD (25)
Python Kubernetes AWS SQL NoSQL Docker IAM EC2 S3 DynamoDB EMR SageMaker Google Cloud Microsoft Azure Hive Hadoop Snowflake Object-Oriented Programming MLOps MLflow Kubeflow Machine Learning NumPy pandas scikit-learn
Skill cluster (9 dimension groups, role-scoped)
Cloud Platforms
AWS S3 Microsoft Azure
MLOps Platforms and Lifecycle
SageMaker MLflow Kubeflow
AI Governance and Model Security
Machine Learning
Containerization and Image Builds
Docker
Deployment Rollouts and Release Control
MLOps
Kubernetes for ML Workloads
Kubernetes
ML Frameworks and Libraries
scikit-learn
Programming Languages for ML Systems
Python
Cross-cutting / unaligned
SQL NoSQL IAM EC2 DynamoDB EMR Google Cloud Hive Hadoop Snowflake Object-Oriented Programming NumPy pandas
Show KRA description ↓
Relocation support if you are moving to Gdansk area from a different part of Poland or from another country Health and well-being benefits: sports costs covered, fully subsidized medical plan including eligible dependents. Summer hours which allow employees to leave the office on Friday at noon all Summer long! Performance Sharing Plan Learning benefits: language training and online courses Financial benefits: group life insurance, disability and accident insurance Company product discount Casual and international work environment 3+ years of experience with Python Experience with Kubernetes and the broader container ecosystem Experience with using AWS services (i.e. IAM, EC2, S3, DynamoBD, EMR, SageMaker) or other public cloud services (Google, Microsoft, etc.) Experience with handling data located in various data sources - SQL, NoSQL databases, Hive, Hadoop, SnowFlake, etc. Experience with designing and building large-scale software and/or data architecture Knowledge of object-oriented programming Knowledge of MLOps tools, like SageMaker, MLflow, Kubeflow, etc. Knowledge of Docker, Kubernetes or other container technologies Knowledge of Machine Learning concepts and related tooling - numpy, pandas, scikit-learn Excellent written and verbal communication skills in technical and non-technical areas

Signals

Skill backend-engineer
0.67
Alias backend-engineer
1.00
KRA engineering-manager
0.37

Post-classification

Centroidupdated · n=30
Alias collision log
New-role queue
New skills captured7
New KRA capturedyes

Captured for admin review

EC2 ML Engineer pending
DynamoDB ML Engineer pending
EMR ML Engineer pending
Google Cloud ML Engineer pending
Object-Oriented Programming ML Engineer pending
NumPy ML Engineer pending
pandas ML Engineer pending
R&R fragment (sim 0.00) ML Engineer pending

Relocation support if you are moving to Gdansk area from a different part of Poland or from another country Health and well-being benefits: sports costs covered, fully subsidized medical plan includin…

Status: completed Created: 2026-05-27T16:32:36.139346Z Updated: 2026-05-27T16:35:02.420682Z API 3 duration: 99282 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

ML Engineer

domain · AI / ML CASE DOMAIN

slug: ml-engineer · id: 3 · source: db

Domain=AI / ML; The JD centers on Python-based software and data architecture with cloud, container, and machine learning tooling, which best matches an ML Engineer rather than a pure MLOps or AI infrastructure role.

Matched skills

PythonKubernetesAWSIAMEC2S3DynamoBDEMRSageMakerSQLNoSQLHiveHadoopSnowFlakeDockernumpypandasscikit-learnMLflowKubeflow

Matched dimensions

Cloud-based software and data architectureMachine learning engineeringMLOps tooling and deploymentContainerized application developmentData engineering across multiple storage systemsObject-oriented programmingTechnical communication

Matched KRAs

Designing and building large-scale software and/or data architectureExperience with handling data located in various data sourcesExperience with Kubernetes and the broader container ecosystemExperience with using AWS servicesKnowledge of MLOps toolsKnowledge of Machine Learning concepts and related tooling

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
5
Skipped

Job description

Are you a tech professional looking for remote work in a global setting? If yes, this job is for you.

Welcome to EPAM Anywhere - a global job platform offering remote work opportunities in the technology sector. Join us to build a career around your lifestyle working on modern projects for global brands and exciting startups.

Currently, we are looking for aRemote Senior Python Developer to join our team.

Responsibilities

Relocation support if you are moving to Gdansk area from a different part of Poland or from another country
Health and well-being benefits: sports costs covered, fully subsidized medical plan including eligible dependents.
Summer hours which allow employees to leave the office on Friday at noon all Summer long!
Performance Sharing Plan
Learning benefits: language training and online courses
Financial benefits: group life insurance, disability and accident insurance
Company product discount
Casual and international work environment


Requirements

3+ years of experience with Python
Experience with Kubernetes and the broader container ecosystem
Experience with using AWS services (i.e. IAM, EC2, S3, DynamoBD, EMR, SageMaker) or other public cloud services (Google, Microsoft, etc.)
Experience with handling data located in various data sources - SQL, NoSQL databases, Hive, Hadoop, SnowFlake, etc.
Experience with designing and building large-scale software and/or data architecture
Knowledge of object-oriented programming
Knowledge of MLOps tools, like SageMaker, MLflow, Kubeflow, etc.
Knowledge of Docker, Kubernetes or other container technologies
Knowledge of Machine Learning concepts and related tooling - numpy, pandas, scikit-learn
Excellent written and verbal communication skills in technical and non-technical areas


We offer

Insurance Coverage
Paid Leaves – including maternity, bereavement, paternity, and special COVID-19 leaves.
Financial assistance for medical crisis
Retiral Benefits – VPF and NPS
Customized Mindfulness and Wellness programs
EPAM Hobby Clubs
Hybrid Work Model
Soft loans to set up workspace at home
Stable workload
Relocation opportunities with ‘EPAM without Borders’ program
Certification trainings for technical and soft skills
Access to unlimited LinkedIn Learning platform
Access to internal learning programs set up by world class trainers
Community networking and idea creation platforms
Mentorship programs
Self-driven career progression tool


This is a remote position and we welcome applications from anywhere in India

Once you apply, you'll receive a confirmation email with a link to EPAM Anywhere platform. Sign up with this link to automate your prescreening, be able to monitor your application statuses, and enjoy a faster job application process.

We accept CVs only in English.

Please note that even though you are applying for this position, you may be offered other projects to join within EPAM Anywhere.

EPAM Anywhere is a part of EPAM Systems, Inc. (NYSE: EPAM). Since 1993, EPAM has leveraged its advanced software engineering heritage to become the foremost global digital transformation services provider.

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

Python Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Python id=5 · python

Aliases — catalog

  • Python (CANONICAL) primary
  • Python 2 (VERSION)
  • Python 2.x (VERSION)
  • Python 3 (VERSION)
  • Python 3.10 (VERSION)
  • Python 3.11 (VERSION)
  • Python 3.12 (VERSION)
  • Python 3.x (VERSION)
  • py (VERSION)
  • py2 (VERSION)
  • py3 (VERSION)
  • python 3 (VERSION)
  • python 3.x (VERSION)
  • python2 (VERSION)
  • python3 (VERSION)
  • python3.x (VERSION)

Context tags (catalog)

API Django FastAPI Flask Jupyter NumPy PEP 8 Pandas REST SQLAlchemy asyncio pandas pip pytest type hints venv virtualenv

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
PSF
License
mit
Year introduced
1991
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
3

Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Security Scripting & DSL Languages Catalog dimension db id 248

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension saved
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kubernetes Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Kubernetes id=726 · kubernetes

Aliases — catalog

  • Kubernetes (CANONICAL) primary
  • Kubernetes 1.0+ (VERSION)
  • Kubernetes 1.x (VERSION)
  • Kubernetes v1 (VERSION)
  • k8s (VERSION)
  • kubernetes 1.x (VERSION)
  • kubernetes latest (VERSION)

Context tags (catalog)

CI/CD Cluster Autoscaler ConfigMap DaemonSet Deployment Docker Grafana Helm Ingress Istio K8s Kubelet Namespace Pod Prometheus RBAC Secret Service StatefulSet containerization deployment etcd kubectl load balancing microservices namespace orchestration persistent storage scalability service mesh

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Container Orchestration Platform
Vendor
Cloud Native Computing Foundation
License
apache_2
Year introduced
2014
Confidence
0.90
Version strategy
SEPARATE_ENTITY
Version tag
1.30

Maturity reasoning: Broadly adopted in cloud-native stacks; Kubernetes appears in a large share of DevOps/SRE job descriptions and is the default orchestration platform across major cloud vendors.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
557
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Container Orchestration Platforms Catalog dimension db id 134

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, DevOps Engineer

  • Kubernetes for ML Workloads Catalog dimension db id 47

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Container Orchestration Platforms
container-orchestration-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
Existing dimension (library) · Role↔dimension saved
AWS Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: AWS id=187 · aws

Aliases — catalog

  • AWS (CANONICAL) primary

Context tags (catalog)

API Gateway AWS CLI Auto Scaling CloudFormation CloudFront CloudTrail CloudWatch Cognito DynamoDB EC2 ECS EKS Elastic Beanstalk Elastic Load Balancing IAM KMS Lambda RDS Route 53 S3 SNS SQS Serverless VPC

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Amazon
License
other_open
Year introduced
2006
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: AWS is a hiring-pipeline staple: it appears in a large share of cloud/DevOps job descriptions and dominates public cloud market share, with broad certification and vendor ecosystem support.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
46
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer, Cyber Security Engineer

  • Vendor Product Families Catalog dimension db id 477

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
IAM Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: IAM id=1217 · iam

Aliases — catalog

  • IAM (CANONICAL)

Context tags (catalog)

ABAC IAM governance MFA OAuth OpenID Connect RBAC SAML SSO access control audit logs directory services identity federation policy management security tokens user provisioning

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Identity And Access Management Platform
Vendor
Amazon Web Services
License
proprietary
Year introduced
2011
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: IAM is a standard cloud/security platform skill; it appears routinely in AWS/Azure/GCP job descriptions and is a core control in vendor docs and compliance frameworks, indicating broad hiring demand.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
923
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
EC2 Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
S3 Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: S3 id=1212 · s3

Aliases — catalog

  • S3 (CANONICAL)

Context tags (catalog)

AWS AWS CLI CORS CloudFormation IAM policies S3 Select bucket data lifecycle encryption event notifications multipart upload object storage static website hosting transfer acceleration versioning

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Storage Platform
Vendor
Amazon
License
proprietary
Year introduced
2006
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Amazon S3 is a default cloud storage service in AWS job descriptions and architecture docs; it remains broadly adopted with no vendor sunset, and is commonly paired with S3-compatible storage rather than replaced.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
919
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Systems Programming Catalog dimension db id 166

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Systems Programming
d_init_02
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DynamoDB Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Amazon DynamoDB id=93 · amazon-dynamodb

Aliases — catalog

  • Amazon DynamoDB (CANONICAL) primary

Context tags (catalog)

AWS SDK DAX GSI LSI NoSQL Streams TTL boto3 conditional writes on-demand capacity partition key provisioned throughput secondary index sort key transactions

Stored enrichment (catalog DB)

Category
Service
Sub-category
Managed Nosql Database Service
Vendor
Amazon Web Services
License
proprietary
Year introduced
2012
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Commonly listed in cloud/backend job descriptions and widely used on AWS; strong vendor adoption and active ecosystem signal broad market demand.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
55
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • NoSQL Databases Catalog dimension db id 19

    Library dimension (catalog)

    Roles linked in library: Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
NoSQL Databases
nosql-databases
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
EMR Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
SageMaker Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SageMaker id=211 · sagemaker

Aliases — catalog

  • SageMaker (CANONICAL) primary

Context tags (catalog)

A/B testing AWS Docker IAM roles Jupyter notebook ML Ops MLOps SageMaker Pipelines SageMaker Studio automated model tuning batch transform boto3 built-in algorithms data labeling data wrangling endpoint deployment feature store ground truth hyperparameter tuning model monitor model registry model training notebook instances pipelines real-time inference reinforcement learning training job

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Ml Platform
Vendor
Amazon
License
apache_2
Year introduced
2017
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: AWS SageMaker appears frequently in ML/MLops job descriptions and is a core managed service in AWS’s AI stack, indicating broad hiring demand rather than niche use.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
175
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • MLOps Platforms and Lifecycle Catalog dimension db id 43

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Existing dimension (library) · Role↔dimension saved
Google Cloud Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Google Cloud Platform id=425 · google-cloud-platform

Aliases — catalog

  • Google Cloud Platform (CANONICAL) primary

Context tags (catalog)

Anthos App Engine Artifact Registry BigQuery Cloud Build Cloud Functions Cloud Monitoring Cloud Pub/Sub Cloud Run Cloud SQL Cloud Spanner Cloud Storage Compute Engine Dataflow Dataproc GCP GKE IAM Kubernetes Kubernetes Engine Pub/Sub Serverless Stackdriver Terraform VPC

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Google
License
other_open
Year introduced
2008
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: GCP appears in many cloud-engineering job descriptions alongside AWS/Azure, and Google continues expanding managed services and certifications, indicating broad hiring demand rather than niche use.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
46
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud & Hosting Providers Catalog dimension db id 414

    Library dimension (catalog)

    Roles linked in library: PHP Backend Developer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer, Cyber Security Engineer

  • Vendor Product Families Catalog dimension db id 477

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud & Hosting Providers
cloud-hosting-providers
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Cloud Provider Platforms
cloud-provider-platforms
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Cloud Security Posture Tools
cloud-security-posture-tools
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Vendor Product Families
vendor-product-families
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Microsoft Azure Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Microsoft Azure id=97 · microsoft-azure

Aliases — catalog

  • Microsoft Azure (CANONICAL) primary

Context tags (catalog)

AKS ARM templates App Service Azure Active Directory Azure App Service Azure Blob Storage Azure Cosmos DB Azure DevOps Azure Functions Azure Kubernetes Service Azure Logic Apps Azure Monitor Azure Resource Manager Azure SQL Azure Virtual Machines Bicep Cloud Services Entra ID Functions IaaS Infrastructure as Code Key Vault Logic Apps PaaS Resource Group Serverless Computing Service Bus Storage Account Virtual Machines cloud migration microservices serverless

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Microsoft
License
other_open
Year introduced
2010
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Azure appears in large volumes of cloud/DevOps job descriptions and is a core hyperscaler alongside AWS/GCP; Microsoft’s continued product investment and broad enterprise adoption signal mainstream demand.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
46
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud & Hosting Providers Catalog dimension db id 414

    Library dimension (catalog)

    Roles linked in library: PHP Backend Developer

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud & Hosting Providers
cloud-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
SQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SQL id=101 · sql

Aliases — catalog

  • SQL (CANONICAL) primary

Context tags (catalog)

ACID CTE DDL DML ETL JOIN MySQL NoSQL OLAP ORM PostgreSQL SQL injection SQLite T-SQL data modeling data warehousing database normalization execution plan indexing joins normalization query optimization stored procedures subquery transaction isolation transaction management window functions

Stored enrichment (catalog DB)

Category
Language
Sub-category
Query Language
Vendor
ANSI
License
unknown
Year introduced
1974
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
97
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Pega Programming Languages & DSLs Catalog dimension db id 267

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
NoSQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: NoSQL id=1346 · nosql

Aliases — catalog

  • NoSQL (CANONICAL)

Context tags (catalog)

CAP theorem Cassandra DynamoDB MongoDB Redis column-family data modeling document store eventual consistency graph database horizontal scaling key-value store query language schema-less sharding

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Database Paradigm
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: NoSQL is broadly listed in job descriptions across backend/data roles, with MongoDB, DynamoDB, and Cassandra appearing as common market signals; it remains a hiring-pipeline staple rather than a niche or sunset tech.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1019
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • NoSQL Databases Catalog dimension db id 19

    Library dimension (catalog)

    Roles linked in library: Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hive Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Hive id=2754 · hive

Aliases — catalog

  • Hive (CANONICAL) primary

Context tags (catalog)

Apache Apache Hive Bucketing ETL HQL Hive Metastore Hive SerDe HiveQL MapReduce SQL SQL-on-Hadoop big data bucketing columnar storage data lakes data warehousing integration metadata partitioning schema evolution

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Local Key Value Store
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2010
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Hive appears in Flutter/mobile JDs and package docs, but JD volume is far below SQLite/Realm and it’s mainly used for local key-value storage in Flutter apps.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
2242
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Local Persistence and Offline Behavior Catalog dimension db id 85

    Library dimension (catalog)

    Roles linked in library: Android Developer, Flutter Developer, Hybrid Mobile Developer, Native Mobile Developer, React Native Developer, iOS Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Local Persistence and Offline Behavior
local-persistence-and-offline-behavior
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hadoop Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Hadoop id=1351 · hadoop

Aliases — catalog

  • Hadoop (CANONICAL)

Context tags (catalog)

Big Data Data Lake Distributed Computing ELT ETL Flume HDFS Hive Kafka MapReduce NoSQL Oozie Pig Spark Sqoop YARN

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Data Processing Framework
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2006
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Job postings still mention Hadoop for legacy big-data stacks, but JD volume has fallen as Spark and cloud warehouses replaced MapReduce-era clusters.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
91
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ETL and ELT Tooling Catalog dimension db id 24

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Snowflake Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Snowflake id=105 · snowflake

Aliases — catalog

  • Snowflake (CANONICAL) primary

Context tags (catalog)

ELT ETL SQL Snowpark Snowpipe Streams Tasks Time Travel VARIANT data sharing data warehouse dbt semi-structured data virtual warehouse zero-copy cloning

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Data Cloud Platform
Vendor
Snowflake Inc.
License
proprietary
Year introduced
2012
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Snowflake appears frequently in data/analytics job postings and is a standard cloud data warehouse platform alongside BigQuery and Redshift.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
113
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Data Warehouses Catalog dimension db id 22

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Data Warehouses
cloud-data-warehouses
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Object-Oriented Programming Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
MLOps Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: MLOps id=1196 · mlops

Aliases — catalog

  • MLOps (CANONICAL)

Context tags (catalog)

A/B testing CI/CD Docker Kubeflow Kubernetes MLflow automation cloud-native data governance data pipeline model deployment monitoring reproducibility scalability versioning

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Mlops
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: MLOps appears in many job descriptions for ML/platform roles and is a standard practice in major cloud vendor docs (AWS, GCP, Azure) for CI/CD, model monitoring, and deployment.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
906
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD for Machine Learning Catalog dimension db id 56

    Library dimension (catalog)

    Roles linked in library: ML Engineer

  • Data Lineage and Metadata Catalog dimension db id 28

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Deployment Rollouts and Release Control Catalog dimension db id 51

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension saved
Data Lineage and Metadata
data-lineage-and-metadata
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment Rollouts and Release Control
deployment-rollouts-and-release-control
Existing dimension (library) · Role↔dimension saved
MLflow Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: MLflow id=214 · mlflow

Aliases — catalog

  • MLflow (CANONICAL) primary

Context tags (catalog)

A/B testing API Databricks ML pipeline UI artifact store artifacts data lineage deployment experiment tracking experiments feature store flavors hyperparameter tuning integration logging model lineage model registry model serving model versioning pipelines reproducibility run tracking scalability tracking training jobs versioning

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Mlops Tool
Vendor
Databricks
License
apache_2
Year introduced
2018
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: MLflow appears frequently in MLOps job descriptions and is a standard open-source model tracking/registry tool; Databricks continues to invest in it, signaling broad adoption rather than niche use.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
1168
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • MLOps Platforms and Lifecycle Catalog dimension db id 43

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Existing dimension (library) · Role↔dimension saved
Kubeflow Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Kubeflow id=213 · kubeflow

Aliases — catalog

  • Kubeflow (CANONICAL) primary
  • Kubeflow 1.x (VERSION)
  • Kubeflow 2.x (VERSION)
  • Kubeflow v1 (VERSION)
  • Kubeflow v2 (VERSION)

Context tags (catalog)

Argo Argo Workflows CI/CD Data preprocessing GPU scheduling Hyperparameter tuning Istio Jupyter notebooks KFServing Katib Kubeflow Pipelines Kubeflow Training Kubernetes ML pipelines MLOps MLflow MinIO Model serving Pipeline components PyTorch Seldon Seldon Core TensorFlow model serving

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Mlops Framework
Vendor
Google
License
apache_2
Year introduced
2017
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Kubeflow appears in some MLOps/ML platform JDs, but far less often than Kubernetes or managed ML platforms; GitHub activity is steady yet adoption remains specialized to ML infrastructure teams.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
1127
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • MLOps Platforms and Lifecycle Catalog dimension db id 43

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Existing dimension (library) · Role↔dimension saved
Docker Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Docker id=61 · docker

Aliases — catalog

  • Docker (CANONICAL) primary

Context tags (catalog)

CI/CD Compose DevOps Docker Compose Docker Swarm Dockerfile Kubernetes build pipeline container container lifecycle container orchestration container registry container security containerization containers image image registry images immutable infrastructure lightweight virtualization microservices networking orchestration port mapping registry scalability service discovery swarm volume volume management

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Containerization Tool
Vendor
Docker, Inc.
License
apache_2
Year introduced
2013
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Docker is a hiring-pipeline staple: it appears in many DevOps, backend, and platform JDs, and remains a standard containerization tool alongside Kubernetes in production stacks.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
63
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Containerization and Image Builds Catalog dimension db id 152

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • Deployment and Cloud Platforms Catalog dimension db id 418

    Library dimension (catalog)

    Roles linked in library: Ruby Backend Developer

  • Deployment and Runtime Configuration Catalog dimension db id 13

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Go Backend Developer, PHP Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Containerization and Image Builds
containerization-and-image-builds
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment and Cloud Platforms
deployment-and-cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment and Runtime Configuration
deployment-and-runtime-configuration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Machine Learning Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Machine Learning id=1356 · machine-learning

Aliases — catalog

  • Machine Learning (CANONICAL)

Context tags (catalog)

Keras PyTorch TensorFlow cross-validation data preprocessing ensemble methods feature engineering hyperparameter tuning model evaluation natural language processing neural networks reinforcement learning scikit-learn supervised learning unsupervised learning

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Machine Learning
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Machine Learning appears in large volumes of job descriptions across data, product, and platform roles, and major cloud vendors (AWS, Google Cloud, Azure) offer dedicated ML services and certifications, indicating broad adoption.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1024
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • AI Governance and Model Security Catalog dimension db id 50

    Library dimension (catalog)

    Roles linked in library: AI Engineer, ML Engineer, MLOps Engineer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
AI Governance and Model Security
ai-governance-and-model-security
Existing dimension (library) · Role↔dimension saved
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
NumPy Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Programming Languages
Sub-category
Data Science Libraries
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
pandas Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Programming Languages
Sub-category
Data Science Libraries
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
scikit-learn Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: scikit-learn id=197 · scikit-learn

Aliases — catalog

  • scikit-learn (CANONICAL) primary

Context tags (catalog)

GridSearchCV K-fold NumPy Pandas Pipeline SVM classification clustering cross-validation cross_validation data_preprocessing ensemble_methods feature engineering feature_importance hyperparameter_tuning imbalanced-learn joblib logistic regression metrics model_selection pipelines predictive_modeling preprocessing random forest regression scoring_metrics train_test_split

Stored enrichment (catalog DB)

Category
Library
Sub-category
Machine Learning Library
Vendor
scikit-learn developers
License
bsd
Year introduced
2007
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: Commonly listed in ML/data science job descriptions and widely used in production Python ML stacks; no vendor sunset or replacement signal, and GitHub activity remains strong.

Skill profile (library / DB)

Skill nature
LIBRARY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
7
Sub-category id
156
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ML Frameworks and Libraries Catalog dimension db id 40

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ML Frameworks and Libraries
ml-frameworks-and-libraries
Existing dimension (library) · Role↔dimension saved

All API 3 persistence rows

Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.

Skill Tag Dimension Skill↔dim Role↔dim Outcome Notes
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension saved
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kubernetes in_db
Container Orchestration Platforms
container-orchestration-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kubernetes in_db
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
Existing dimension (library) · Role↔dimension saved
AWS in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
AWS in_db
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
IAM in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
S3 in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
S3 in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
S3 in_db
Systems Programming
d_init_02
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DynamoDB new
NoSQL Databases
nosql-databases
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
SageMaker in_db
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Existing dimension (library) · Role↔dimension saved
Google Cloud new
Cloud & Hosting Providers
cloud-hosting-providers
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Google Cloud new
Cloud Provider Platforms
cloud-provider-platforms
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Google Cloud new
Cloud Security Posture Tools
cloud-security-posture-tools
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Google Cloud new
Vendor Product Families
vendor-product-families
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Microsoft Azure in_db
Cloud & Hosting Providers
cloud-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Microsoft Azure in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
SQL in_db
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
NoSQL in_db
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hive in_db
Local Persistence and Offline Behavior
local-persistence-and-offline-behavior
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hadoop in_db
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Snowflake in_db
Cloud Data Warehouses
cloud-data-warehouses
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MLOps in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension saved
MLOps in_db
Data Lineage and Metadata
data-lineage-and-metadata
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MLOps in_db
Deployment Rollouts and Release Control
deployment-rollouts-and-release-control
Existing dimension (library) · Role↔dimension saved
MLflow in_db
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Existing dimension (library) · Role↔dimension saved
Kubeflow in_db
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Existing dimension (library) · Role↔dimension saved
Docker in_db
Containerization and Image Builds
containerization-and-image-builds
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker in_db
Deployment and Cloud Platforms
deployment-and-cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker in_db
Deployment and Runtime Configuration
deployment-and-runtime-configuration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Machine Learning in_db
AI Governance and Model Security
ai-governance-and-model-security
Existing dimension (library) · Role↔dimension saved
Machine Learning in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
scikit-learn in_db
ML Frameworks and Libraries
ml-frameworks-and-libraries
Existing dimension (library) · Role↔dimension saved

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed EC2 | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed EMR | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Object-Oriented Programming | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed NumPy | type=Programming Languages subtype=Data Science Libraries nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed pandas | type=Programming Languages subtype=Data Science Libraries nature=TOOL lifespan=MULTI_YEAR
dimension_skill_link_proposed DynamoDB ↔ NoSQL Databases
dimension_skill_link_proposed Google Cloud ↔ Cloud & Hosting Providers
dimension_skill_link_proposed Google Cloud ↔ Cloud Provider Platforms
dimension_skill_link_proposed Google Cloud ↔ Cloud Security Posture Tools
dimension_skill_link_proposed Google Cloud ↔ Vendor Product Families
nano JD Parser — gpt-4.1-nano click to toggle
RoleRemote Senior Python Developer
CompanyEPAM Systems, Inc.
Experience3+ years of experience with Python
DomainIT Services & Consulting
Location India (remote)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "EPAM Anywhere is a part",
      "last_5_words": "transformation services provider."
    },
    "text": "EPAM Anywhere is a part of EPAM Systems, Inc. (NYSE: EPAM). Since 1993, EPAM has leveraged its advanced software engineering heritage to become the foremost global digital transformation services provider.",
    "word_count": 32
  },
  "certifications": [],
  "company_name": "EPAM Systems, Inc.",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "ITES",
        "BPO",
        "Tech Consulting"
      ],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": null,
    "min": 3,
    "raw": "3+ years of experience with Python"
  },
  "job_locations": [
    {
      "aliases": [],
      "city": null,
      "country": "India",
      "state": null,
      "work_mode": "remote"
    }
  ],
  "role": "Remote Senior Python Developer",
  "role_aliases": [
    "Senior Python Developer",
    "Python Developer",
    "Software Engineer"
  ],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 7,
      "heading": "Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Relocation support if you are",
        "last_5_words": "international work environment"
      },
      "text": "Relocation support if you are moving to Gdansk area from a different part of Poland or from another country\nHealth and well-being benefits: sports costs covered, fully subsidized medical plan including eligible dependents.\nSummer hours which allow employees to leave the office on Friday at noon all Summer long!\nPerformance Sharing Plan\nLearning benefits: language training and online courses\nFinancial benefits: group life insurance, disability and accident insurance\nCompany product discount\nCasual and international work environment",
      "word_count": 66
    },
    {
      "bullet_count": 10,
      "heading": "Requirements",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "3+ years of experience with",
        "last_5_words": "technical and non-technical areas"
      },
      "text": "3+ years of experience with Python\nExperience with Kubernetes and the broader container ecosystem\nExperience with using AWS services (i.e. IAM, EC2, S3, DynamoBD, EMR, SageMaker) or other public cloud services (Google, Microsoft, etc.)\nExperience with handling data located in various data sources - SQL, NoSQL databases, Hive, Hadoop, SnowFlake, etc.\nExperience with designing and building large-scale software and/or data architecture\nKnowledge of object-oriented programming\nKnowledge of MLOps tools, like SageMaker, MLflow, Kubeflow, etc.\nKnowledge of Docker, Kubernetes or other container technologies\nKnowledge of Machine Learning concepts and related tooling - numpy, pandas, scikit-learn\nExcellent written and verbal communication skills in technical and non-technical areas",
      "word_count": 139
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "Kubernetes"
    },
    {
      "is_primary": true,
      "skill_name": "AWS"
    },
    {
      "is_primary": false,
      "skill_name": "IAM"
    },
    {
      "is_primary": false,
      "skill_name": "EC2"
    },
    {
      "is_primary": false,
      "skill_name": "S3"
    },
    {
      "is_primary": false,
      "skill_name": "DynamoDB"
    },
    {
      "is_primary": false,
      "skill_name": "EMR"
    },
    {
      "is_primary": false,
      "skill_name": "SageMaker"
    },
    {
      "is_primary": false,
      "skill_name": "Google Cloud"
    },
    {
      "is_primary": false,
      "skill_name": "Microsoft Azure"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "NoSQL"
    },
    {
      "is_primary": false,
      "skill_name": "Hive"
    },
    {
      "is_primary": false,
      "skill_name": "Hadoop"
    },
    {
      "is_primary": false,
      "skill_name": "Snowflake"
    },
    {
      "is_primary": false,
      "skill_name": "Object-Oriented Programming"
    },
    {
      "is_primary": false,
      "skill_name": "MLOps"
    },
    {
      "is_primary": false,
      "skill_name": "MLflow"
    },
    {
      "is_primary": false,
      "skill_name": "Kubeflow"
    },
    {
      "is_primary": true,
      "skill_name": "Docker"
    },
    {
      "is_primary": false,
      "skill_name": "Machine Learning"
    },
    {
      "is_primary": false,
      "skill_name": "NumPy"
    },
    {
      "is_primary": false,
      "skill_name": "pandas"
    },
    {
      "is_primary": false,
      "skill_name": "scikit-learn"
    }
  ],
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    "display_name": "Remote Senior Python Developer",
    "rationale": null,
    "role_aliases": [
      "Senior Python Developer",
      "Python Developer",
      "Software Engineer"
    ],
    "role_archetype": "Engineering",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "EPAM Anywhere is a part",
        "last_5_words": "transformation services provider."
      },
      "text": "EPAM Anywhere is a part of EPAM Systems, Inc. (NYSE: EPAM). Since 1993, EPAM has leveraged its advanced software engineering heritage to become the foremost global digital transformation services provider.",
      "word_count": 32
    },
    "certifications": [],
    "company_name": "EPAM Systems, Inc.",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "ITES",
          "BPO",
          "Tech Consulting"
        ],
        "domain": "IT Services \u0026 Consulting"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": null,
      "min": 3,
      "raw": "3+ years of experience with Python"
    },
    "job_locations": [
      {
        "aliases": [],
        "city": null,
        "country": "India",
        "state": null,
        "work_mode": "remote"
      }
    ],
    "role": "Remote Senior Python Developer",
    "role_aliases": [
      "Senior Python Developer",
      "Python Developer",
      "Software Engineer"
    ],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 7,
        "heading": "Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Relocation support if you are",
          "last_5_words": "international work environment"
        },
        "text": "Relocation support if you are moving to Gdansk area from a different part of Poland or from another country\nHealth and well-being benefits: sports costs covered, fully subsidized medical plan including eligible dependents.\nSummer hours which allow employees to leave the office on Friday at noon all Summer long!\nPerformance Sharing Plan\nLearning benefits: language training and online courses\nFinancial benefits: group life insurance, disability and accident insurance\nCompany product discount\nCasual and international work environment",
        "word_count": 66
      },
      {
        "bullet_count": 10,
        "heading": "Requirements",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "3+ years of experience with",
          "last_5_words": "technical and non-technical areas"
        },
        "text": "3+ years of experience with Python\nExperience with Kubernetes and the broader container ecosystem\nExperience with using AWS services (i.e. IAM, EC2, S3, DynamoBD, EMR, SageMaker) or other public cloud services (Google, Microsoft, etc.)\nExperience with handling data located in various data sources - SQL, NoSQL databases, Hive, Hadoop, SnowFlake, etc.\nExperience with designing and building large-scale software and/or data architecture\nKnowledge of object-oriented programming\nKnowledge of MLOps tools, like SageMaker, MLflow, Kubeflow, etc.\nKnowledge of Docker, Kubernetes or other container technologies\nKnowledge of Machine Learning concepts and related tooling - numpy, pandas, scikit-learn\nExcellent written and verbal communication skills in technical and non-technical areas",
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    ],
    "urls": []
  },
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  "rejection_reason": null,
  "run_id": "67f0e487-75be-4e75-8669-b0e788dfe236",
  "stage3_signals": {
    "alias_found": true,
    "alias_match_roles": [
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        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": null,
        "matched_skills": null,
        "role_id": 1,
        "score": 1.0,
        "slug": "backend-engineer",
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      },
      {
        "display_name": "Python Backend Developer",
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        "matched_count": null,
        "matched_skills": null,
        "role_id": 80,
        "score": 1.0,
        "slug": "python-backend-developer",
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      }
    ],
    "kra_match_roles": [
      {
        "display_name": "Engineering Manager",
        "kra_matches": [
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "Excellent written and verbal communication skills in technical and non-technical areas",
            "similarity": 0.3997
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          {
            "kra_text": "support hiring and onboarding",
            "sentence": "Casual and international work environment",
            "similarity": 0.3595
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          {
            "kra_text": "support hiring and onboarding",
            "sentence": "Financial benefits: group life insurance, disability and accident insurance",
            "similarity": 0.3413
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        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 121,
        "score": 0.3668,
        "slug": "engineering-manager",
        "total_count": null
      },
      {
        "display_name": "React Frontend Developer",
        "kra_matches": [
          {
            "kra_text": "translate product and design requirements",
            "sentence": "Excellent written and verbal communication skills in technical and non-technical areas",
            "similarity": 0.3253
          },
          {
            "kra_text": "translate product and design requirements",
            "sentence": "Casual and international work environment",
            "similarity": 0.3073
          },
          {
            "kra_text": "translate product and design requirements",
            "sentence": "Learning benefits: language training and online courses",
            "similarity": 0.2964
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 89,
        "score": 0.3097,
        "slug": "react-frontend-developer",
        "total_count": null
      },
      {
        "display_name": "Flutter Developer",
        "kra_matches": [
          {
            "kra_text": "translate product and design requirements",
            "sentence": "Excellent written and verbal communication skills in technical and non-technical areas",
            "similarity": 0.3253
          },
          {
            "kra_text": "translate product and design requirements",
            "sentence": "Casual and international work environment",
            "similarity": 0.3073
          },
          {
            "kra_text": "translate product and design requirements",
            "sentence": "Learning benefits: language training and online courses",
            "similarity": 0.2964
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 74,
        "score": 0.3097,
        "slug": "flutter-developer",
        "total_count": null
      },
      {
        "display_name": ".NET Backend Developer",
        "kra_matches": [
          {
            "kra_text": "service-level technical collaboration",
            "sentence": "Excellent written and verbal communication skills in technical and non-technical areas",
            "similarity": 0.3998
          },
          {
            "kra_text": "internal and third-party system integration",
            "sentence": "Casual and international work environment",
            "similarity": 0.2877
          },
          {
            "kra_text": "service-level technical collaboration",
            "sentence": "Learning benefits: language training and online courses",
            "similarity": 0.2279
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 83,
        "score": 0.3051,
        "slug": "dotnet-backend-developer",
        "total_count": null
      },
      {
        "display_name": "Cloud Architect",
        "kra_matches": [
          {
            "kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
            "sentence": "Excellent written and verbal communication skills in technical and non-technical areas",
            "similarity": 0.3712
          },
          {
            "kra_text": "Designs backup policies, cross-region replication, and disaster recovery runbooks to meet defined RTO and RPO targets for critical workloads.",
            "sentence": "Financial benefits: group life insurance, disability and accident insurance",
            "similarity": 0.272
          },
          {
            "kra_text": "Establishes cloud environment standards including VPC topology, workload placement policies, resource tagging taxonomies, and account structure.",
            "sentence": "Casual and international work environment",
            "similarity": 0.2508
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 9,
        "score": 0.298,
        "slug": "cloud-architect",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 4,
        "matched_skills": [
          "AWS",
          "Docker",
          "NoSQL",
          "Python"
        ],
        "role_id": 1,
        "score": 0.6667,
        "slug": "backend-engineer",
        "total_count": 6
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "AWS",
          "Kubernetes",
          "Python"
        ],
        "role_id": 3,
        "score": 0.5,
        "slug": "ml-engineer",
        "total_count": 6
      },
      {
        "display_name": "DevOps Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "AWS",
          "Docker",
          "Kubernetes"
        ],
        "role_id": 10,
        "score": 0.5,
        "slug": "devops-engineer",
        "total_count": 6
      },
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "AWS",
          "Python",
          "SQL"
        ],
        "role_id": 2,
        "score": 0.5,
        "slug": "data-engineer",
        "total_count": 6
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "AWS",
          "Kubernetes",
          "Python"
        ],
        "role_id": 16,
        "score": 0.5,
        "slug": "ml-ops-engineer",
        "total_count": 6
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "ML Engineer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 3,
      "score": 0.91,
      "slug": "ml-engineer",
      "total_count": null
    },
    "confidence": 0.91,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "Cloud-based software and data architecture",
      "Machine learning engineering",
      "MLOps tooling and deployment",
      "Containerized application development",
      "Data engineering across multiple storage systems",
      "Object-oriented programming",
      "Technical communication"
    ],
    "matched_kras": [
      "Designing and building large-scale software and/or data architecture",
      "Experience with handling data located in various data sources",
      "Experience with Kubernetes and the broader container ecosystem",
      "Experience with using AWS services",
      "Knowledge of MLOps tools",
      "Knowledge of Machine Learning concepts and related tooling"
    ],
    "matched_skills": [
      "Python",
      "Kubernetes",
      "AWS",
      "IAM",
      "EC2",
      "S3",
      "DynamoBD",
      "EMR",
      "SageMaker",
      "SQL",
      "NoSQL",
      "Hive",
      "Hadoop",
      "SnowFlake",
      "Docker",
      "numpy",
      "pandas",
      "scikit-learn",
      "MLflow",
      "Kubeflow"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=AI / ML; The JD centers on Python-based software and data architecture with cloud, container, and machine learning tooling, which best matches an ML Engineer rather than a pure MLOps or AI infrastructure role.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 30,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": {
      "best_kra_similarity": 0.0,
      "queue_id": 1540,
      "r_and_r_preview": "Relocation support if you are moving to Gdansk area from a different part of Poland or from another country\nHealth and well-being benefits: sports costs covered, fully subsidized medical plan includin",
      "role_display_name": "ML Engineer",
      "role_slug": "ml-engineer",
      "status": "pending"
    },
    "new_skills_attached": [
      {
        "is_primary": false,
        "queue_id": 20673,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "EC2",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20674,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "DynamoDB",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20675,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "EMR",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20676,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Google Cloud",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20677,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "Object-Oriented Programming",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20678,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "NumPy",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20679,
        "role_display_name": "ML Engineer",
        "role_slug": "ml-engineer",
        "skill_name": "pandas",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
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    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 67,
      "existing_alias_text": "Python",
      "input_term": "Python",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "Python",
        "id": 5,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "python",
        "sub_category_id": 96,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1267,
      "existing_alias_text": "Kubernetes",
      "input_term": "Kubernetes",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Kubernetes",
        "id": 726,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "kubernetes",
        "sub_category_id": 557,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 406,
      "existing_alias_text": "AWS",
      "input_term": "AWS",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "AWS",
        "id": 187,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "aws",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1853,
      "existing_alias_text": "IAM",
      "input_term": "IAM",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "IAM",
        "id": 1217,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "iam",
        "sub_category_id": 923,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1848,
      "existing_alias_text": "S3",
      "input_term": "S3",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "S3",
        "id": 1212,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "s3",
        "sub_category_id": 919,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": null,
      "existing_alias_text": null,
      "input_term": "DynamoDB",
      "matched_canonical": {
        "category_id": 11,
        "display_name": "Amazon DynamoDB",
        "id": 93,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "amazon-dynamodb",
        "sub_category_id": 55,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_display_name"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 463,
      "existing_alias_text": "SageMaker",
      "input_term": "SageMaker",
      "matched_canonical": {
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        "display_name": "SageMaker",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "sagemaker",
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        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 741,
      "existing_alias_text": "Google Cloud Platform",
      "input_term": "Google Cloud",
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        "display_name": "Google Cloud Platform",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "google-cloud-platform",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 258,
      "existing_alias_text": "Microsoft Azure",
      "input_term": "Microsoft Azure",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Microsoft Azure",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "microsoft-azure",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 271,
      "existing_alias_text": "SQL",
      "input_term": "SQL",
      "matched_canonical": {
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        "display_name": "SQL",
        "id": 101,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "sql",
        "sub_category_id": 97,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
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        },
        {
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        },
        {
          "display_name": "Node.js Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Python Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
          "id": 87,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms for AI Deployment",
        "id": 211,
        "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
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        "source": "db"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "AI Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ai-engineer",
          "source": "db"
        }
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    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Provider Platforms",
        "id": 131,
        "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
        "slug": "cloud-provider-platforms",
        "source": "db"
      },
      "input_skill": "AWS",
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      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
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        {
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          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Security Posture Tools",
        "id": 64,
        "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
        "slug": "cloud-security-posture-tools",
        "source": "db"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": "Cloud Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
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        {
          "display_name": "Cyber Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
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      ]
    },
    {
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        "difficulty_hint": "well_known",
        "display_name": "Vendor Product Families",
        "id": 477,
        "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
        "slug": "vendor-product-families",
        "source": "db"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
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          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
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        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "IAM",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms",
        "id": 20,
        "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
        "slug": "cloud-platforms",
        "source": "db"
      },
      "input_skill": "S3",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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        {
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          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
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        {
          "display_name": "Cyber Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
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        },
        {
          "display_name": "Data Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
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        },
        {
          "display_name": "Fullstack Developer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        },
        {
          "display_name": "Go Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Java Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "java-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Kotlin Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "ML Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
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        },
        {
          "display_name": "MLOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
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        {
          "display_name": "Node.js Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Python Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
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        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "S3",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Systems Programming",
        "id": 166,
        "rationale": "Systems programming covers low-level software development where performance, memory safety, and direct control over resources matter. Rust fits here because it is commonly used for OS-adjacent services, infrastructure components, and other performance-sensitive systems code.",
        "slug": "d_init_02",
        "source": "db"
      },
      "input_skill": "S3",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "NoSQL Databases",
        "id": 19,
        "rationale": "Models and manages data using non-relational database systems.",
        "slug": "nosql-databases",
        "source": "db"
      },
      "input_skill": "DynamoDB",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
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        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "MLOps Platforms and Lifecycle",
        "id": 43,
        "rationale": "End-to-end managed platforms used to train, deploy, register, and govern models across their lifecycle. This is the operational control plane for production ML workflows.",
        "slug": "mlops-platforms-and-lifecycle",
        "source": "db"
      },
      "input_skill": "SageMaker",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud \u0026 Hosting Providers",
        "id": 414,
        "rationale": "Knowledge of major cloud and hosting vendor platforms for deploying and managing PHP applications.",
        "slug": "cloud-hosting-providers",
        "source": "db"
      },
      "input_skill": "Google Cloud",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "PHP Backend Developer",
          "id": 86,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "php-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Provider Platforms",
        "id": 131,
        "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
        "slug": "cloud-provider-platforms",
        "source": "db"
      },
      "input_skill": "Google Cloud",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        },
        {
          "display_name": "Cloud Security Engineer",
          "id": 23,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Security Posture Tools",
        "id": 64,
        "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
        "slug": "cloud-security-posture-tools",
        "source": "db"
      },
      "input_skill": "Google Cloud",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": "Cloud Security Engineer",
          "id": 23,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        },
        {
          "display_name": "Cyber Security Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Vendor Product Families",
        "id": 477,
        "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
        "slug": "vendor-product-families",
        "source": "db"
      },
      "input_skill": "Google Cloud",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
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          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud \u0026 Hosting Providers",
        "id": 414,
        "rationale": "Knowledge of major cloud and hosting vendor platforms for deploying and managing PHP applications.",
        "slug": "cloud-hosting-providers",
        "source": "db"
      },
      "input_skill": "Microsoft Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "PHP Backend Developer",
          "id": 86,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "php-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms",
        "id": 20,
        "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
        "slug": "cloud-platforms",
        "source": "db"
      },
      "input_skill": "Microsoft Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
          "id": 83,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "dotnet-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Backend Developer",
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          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
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        },
        {
          "display_name": "Cyber Security Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        },
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        },
        {
          "display_name": "Go Backend Developer",
          "id": 81,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Java Backend Developer",
          "id": 79,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "java-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Kotlin Backend Developer",
          "id": 84,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "ML Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
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        },
        {
          "display_name": "MLOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        },
        {
          "display_name": "Node.js Backend Developer",
          "id": 82,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Python Backend Developer",
          "id": 80,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
          "id": 87,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Pega Programming Languages \u0026 DSLs",
        "id": 267,
        "rationale": "Programming languages and domain-specific languages used in Pega development.",
        "slug": "pega-programming-languages-dsls",
        "source": "db"
      },
      "input_skill": "SQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Pega Developer",
          "id": 24,
          "rationale": null,
          "role_archetype": null,
          "slug": "pega-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages \u0026 DSLs",
        "id": 475,
        "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
        "slug": "programming-languages-dsls",
        "source": "db"
      },
      "input_skill": "SQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
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          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for Data Work",
        "id": 21,
        "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
        "slug": "programming-languages-for-data-work",
        "source": "db"
      },
      "input_skill": "SQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "NoSQL Databases",
        "id": 19,
        "rationale": "Models and manages data using non-relational database systems.",
        "slug": "nosql-databases",
        "source": "db"
      },
      "input_skill": "NoSQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Local Persistence and Offline Behavior",
        "id": 85,
        "rationale": "On-device storage used for caching, offline support, and durable client state. This cluster is coherent because iOS apps often need to preserve user progress and data when connectivity is limited.",
        "slug": "local-persistence-and-offline-behavior",
        "source": "db"
      },
      "input_skill": "Hive",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Android Developer",
          "id": 4,
          "rationale": null,
          "role_archetype": null,
          "slug": "android-engineer",
          "source": "db"
        },
        {
          "display_name": "Flutter Developer",
          "id": 74,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "flutter-developer",
          "source": "db"
        },
        {
          "display_name": "Hybrid Mobile Developer",
          "id": 11,
          "rationale": null,
          "role_archetype": null,
          "slug": "hybrid-mobile-developer",
          "source": "db"
        },
        {
          "display_name": "Native Mobile Developer",
          "id": 75,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "native-mobile-developer",
          "source": "db"
        },
        {
          "display_name": "React Native Developer",
          "id": 73,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "react-native-developer",
          "source": "db"
        },
        {
          "display_name": "iOS Developer",
          "id": 6,
          "rationale": null,
          "role_archetype": null,
          "slug": "ios-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "ETL and ELT Tooling",
        "id": 24,
        "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
        "slug": "etl-and-elt-tooling",
        "source": "db"
      },
      "input_skill": "Hadoop",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
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    {
      "aliases_in_db": [
        {
          "alias_text": "Kubeflow",
          "alias_type": "CANONICAL",
          "id": 465,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Kubeflow 1.x",
          "alias_type": "VERSION",
          "id": 468,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Kubeflow 2.x",
          "alias_type": "VERSION",
          "id": 469,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Kubeflow v1",
          "alias_type": "VERSION",
          "id": 466,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Kubeflow v2",
          "alias_type": "VERSION",
          "id": 467,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 5,
        "display_name": "Kubeflow",
        "id": 213,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "kubeflow",
        "sub_category_id": 1127,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "MLOps Platforms and Lifecycle",
            "id": 43,
            "rationale": "End-to-end managed platforms used to train, deploy, register, and govern models across their lifecycle. This is the operational control plane for production ML workflows.",
            "slug": "mlops-platforms-and-lifecycle",
            "source": "db"
          },
          "input_skill": "Kubeflow",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Kubeflow",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Docker",
          "alias_type": "CANONICAL",
          "id": 198,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 13,
        "display_name": "Docker",
        "id": 61,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "docker",
        "sub_category_id": 63,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Containerization and Image Builds",
            "id": 152,
            "rationale": "Container image creation, tagging, hardening, and registry workflows used to package services for deployment. This is coherent because DevOps often owns the build-to-image path that feeds runtime environments.",
            "slug": "containerization-and-image-builds",
            "source": "db"
          },
          "input_skill": "Docker",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Deployment and Cloud Platforms",
            "id": 418,
            "rationale": "Platform-as-a-Service and container environments for deploying Ruby applications.",
            "slug": "deployment-and-cloud-platforms",
            "source": "db"
          },
          "input_skill": "Docker",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Ruby Backend Developer",
              "id": 85,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "ruby-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Deployment and Runtime Configuration",
            "id": 13,
            "rationale": "Configuration and release artifacts that control how backend services run in environments. Includes environment variables, manifests, feature flags, and release-safe configuration management.",
            "slug": "deployment-and-runtime-configuration",
            "source": "db"
          },
          "input_skill": "Docker",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": ".NET Backend Developer",
              "id": 83,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "dotnet-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Backend Developer",
              "id": 1,
              "rationale": null,
              "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
              "slug": "backend-engineer",
              "source": "db"
            },
            {
              "display_name": "Go Backend Developer",
              "id": 81,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "go-backend-developer",
              "source": "db"
            },
            {
              "display_name": "PHP Backend Developer",
              "id": 86,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "php-backend-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Docker",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Machine Learning",
          "alias_type": "CANONICAL",
          "id": 2015,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 2,
        "display_name": "Machine Learning",
        "id": 1356,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "machine-learning",
        "sub_category_id": 1024,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "AI Governance and Model Security",
            "id": 50,
            "rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
            "slug": "ai-governance-and-model-security",
            "source": "db"
          },
          "input_skill": "Machine Learning",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AI Engineer",
              "id": 13,
              "rationale": null,
              "role_archetype": null,
              "slug": "ai-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "Machine Learning",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Machine Learning",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "NumPy",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Programming Languages",
          "skill_nature": "TOOL",
          "sub_category": "Data Science Libraries",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "numpy",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "pandas",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Programming Languages",
          "skill_nature": "TOOL",
          "sub_category": "Data Science Libraries",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "pandas",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "scikit-learn",
          "alias_type": "CANONICAL",
          "id": 449,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 7,
        "display_name": "scikit-learn",
        "id": 197,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LIBRARY",
        "slug": "scikit-learn",
        "sub_category_id": 156,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "ML Frameworks and Libraries",
            "id": 40,
            "rationale": "Core libraries used to define models, train them, run inference, and evaluate predictive performance. These frameworks shape how ML engineers express model architectures and training loops.",
            "slug": "ml-frameworks-and-libraries",
            "source": "db"
          },
          "input_skill": "scikit-learn",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "scikit-learn",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "EC2",
    "EMR",
    "Object-Oriented Programming",
    "NumPy",
    "pandas"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "ML Engineer",
    "id": 3,
    "rationale": "Domain=AI / ML; The JD centers on Python-based software and data architecture with cloud, container, and machine learning tooling, which best matches an ML Engineer rather than a pure MLOps or AI infrastructure role.",
    "role_archetype": null,
    "slug": "ml-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Kubernetes",
      "tag": "in_db"
    },
    {
      "skill": "AWS",
      "tag": "in_db"
    },
    {
      "skill": "IAM",
      "tag": "in_db"
    },
    {
      "skill": "EC2",
      "tag": "new"
    },
    {
      "skill": "S3",
      "tag": "in_db"
    },
    {
      "skill": "DynamoDB",
      "tag": "in_db"
    },
    {
      "skill": "EMR",
      "tag": "new"
    },
    {
      "skill": "SageMaker",
      "tag": "in_db"
    },
    {
      "skill": "Google Cloud",
      "tag": "in_db"
    },
    {
      "skill": "Microsoft Azure",
      "tag": "in_db"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "NoSQL",
      "tag": "in_db"
    },
    {
      "skill": "Hive",
      "tag": "in_db"
    },
    {
      "skill": "Hadoop",
      "tag": "in_db"
    },
    {
      "skill": "Snowflake",
      "tag": "in_db"
    },
    {
      "skill": "Object-Oriented Programming",
      "tag": "new"
    },
    {
      "skill": "MLOps",
      "tag": "in_db"
    },
    {
      "skill": "MLflow",
      "tag": "in_db"
    },
    {
      "skill": "Kubeflow",
      "tag": "in_db"
    },
    {
      "skill": "Docker",
      "tag": "in_db"
    },
    {
      "skill": "Machine Learning",
      "tag": "in_db"
    },
    {
      "skill": "NumPy",
      "tag": "new"
    },
    {
      "skill": "pandas",
      "tag": "new"
    },
    {
      "skill": "scikit-learn",
      "tag": "in_db"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Scripting \u0026 DSL Languages",
          "id": 248,
          "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
          "slug": "cloud-security-scripting-dsl-languages",
          "source": "db"
        },
        "dimension_id": 248,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
          "id": 59,
          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for XR",
          "id": 97,
          "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
          "slug": "programming-languages-for-xr",
          "source": "db"
        },
        "dimension_id": 97,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AR/VR Engineer",
            "id": 8,
            "rationale": null,
            "role_archetype": null,
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          "source": "db"
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        "dimension_id": 290,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Python Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
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        "skipped_reason": null
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      {
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            "slug": "ml-ops-engineer",
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          "source": "db"
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        "matched_chosen_role": true,
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        "role_dimension_saved": true,
        "roles_from_db": [
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          {
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          },
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            "slug": "devops-engineer",
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          },
          {
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            "slug": "full-stack-engineer",
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          {
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          },
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            "source": "db"
          },
          {
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
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        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
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        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms for AI Deployment",
          "id": 211,
          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
          "slug": "cloud-platforms-for-ai-deployment",
          "source": "db"
        },
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        "input_skill": "AWS",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
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            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
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        "dimension": {
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          "source": "db"
        },
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        "input_skill": "AWS",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
          {
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          },
          {
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            "slug": "cloud-security-engineer",
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        ],
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          "difficulty_hint": "well_known",
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          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
          {
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            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
          {
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            "slug": "engineering-manager",
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          "slug": "d_init_01",
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        "input_skill": "IAM",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
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            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
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          {
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            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
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          },
          {
            "display_name": "DevOps Engineer",
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            "slug": "devops-engineer",
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          },
          {
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            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
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          {
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            "rationale": null,
            "role_archetype": "Engineering",
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            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
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            "source": "db"
          },
          {
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            "rationale": null,
            "role_archetype": "Engineering",
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          {
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            "rationale": null,
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            "source": "db"
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          {
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        "skill_dimension_saved": true,
        "skill_id": 1212,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1212,
        "skill_tag": "in_db",
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          "source": "db"
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        "dimension_id": 166,
        "input_skill": "S3",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1212,
        "skill_tag": "in_db",
        "skipped_reason": null
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          "source": "db"
        },
        "dimension_id": 19,
        "input_skill": "DynamoDB",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
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            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
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        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
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      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "MLOps Platforms and Lifecycle",
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          "rationale": "End-to-end managed platforms used to train, deploy, register, and govern models across their lifecycle. This is the operational control plane for production ML workflows.",
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        },
        "dimension_id": 43,
        "input_skill": "SageMaker",
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        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
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          },
          {
            "display_name": "MLOps Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
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        ],
        "skill_dimension_saved": true,
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        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud \u0026 Hosting Providers",
          "id": 414,
          "rationale": "Knowledge of major cloud and hosting vendor platforms for deploying and managing PHP applications.",
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          "source": "db"
        },
        "dimension_id": 414,
        "input_skill": "Google Cloud",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "PHP Backend Developer",
            "id": 86,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Provider Platforms",
          "id": 131,
          "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
          "slug": "cloud-provider-platforms",
          "source": "db"
        },
        "dimension_id": 131,
        "input_skill": "Google Cloud",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Posture Tools",
          "id": 64,
          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
        },
        "dimension_id": 64,
        "input_skill": "Google Cloud",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Vendor Product Families",
          "id": 477,
          "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
          "slug": "vendor-product-families",
          "source": "db"
        },
        "dimension_id": 477,
        "input_skill": "Google Cloud",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud \u0026 Hosting Providers",
          "id": 414,
          "rationale": "Knowledge of major cloud and hosting vendor platforms for deploying and managing PHP applications.",
          "slug": "cloud-hosting-providers",
          "source": "db"
        },
        "dimension_id": 414,
        "input_skill": "Microsoft Azure",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "PHP Backend Developer",
            "id": 86,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 97,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms",
          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "Microsoft Azure",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 97,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Pega Programming Languages \u0026 DSLs",
          "id": 267,
          "rationale": "Programming languages and domain-specific languages used in Pega development.",
          "slug": "pega-programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 267,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Pega Developer",
            "id": 24,
            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "NoSQL Databases",
          "id": 19,
          "rationale": "Models and manages data using non-relational database systems.",
          "slug": "nosql-databases",
          "source": "db"
        },
        "dimension_id": 19,
        "input_skill": "NoSQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1346,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Local Persistence and Offline Behavior",
          "id": 85,
          "rationale": "On-device storage used for caching, offline support, and durable client state. This cluster is coherent because iOS apps often need to preserve user progress and data when connectivity is limited.",
          "slug": "local-persistence-and-offline-behavior",
          "source": "db"
        },
        "dimension_id": 85,
        "input_skill": "Hive",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Android Developer",
            "id": 4,
            "rationale": null,
            "role_archetype": null,
            "slug": "android-engineer",
            "source": "db"
          },
          {
            "display_name": "Flutter Developer",
            "id": 74,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "flutter-developer",
            "source": "db"
          },
          {
            "display_name": "Hybrid Mobile Developer",
            "id": 11,
            "rationale": null,
            "role_archetype": null,
            "slug": "hybrid-mobile-developer",
            "source": "db"
          },
          {
            "display_name": "Native Mobile Developer",
            "id": 75,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "native-mobile-developer",
            "source": "db"
          },
          {
            "display_name": "React Native Developer",
            "id": 73,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "react-native-developer",
            "source": "db"
          },
          {
            "display_name": "iOS Developer",
            "id": 6,
            "rationale": null,
            "role_archetype": null,
            "slug": "ios-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 2754,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "Hadoop",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1351,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Data Warehouses",
          "id": 22,
          "rationale": "Managed analytical storage and compute platforms used for curated datasets, reporting, and downstream analytics. These systems are central to data modeling, performance tuning, and cost-aware query design.",
          "slug": "cloud-data-warehouses",
          "source": "db"
        },
        "dimension_id": 22,
        "input_skill": "Snowflake",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 105,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD for Machine Learning",
          "id": 56,
          "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
          "slug": "ci-cd-for-machine-learning",
          "source": "db"
        },
        "dimension_id": 56,
        "input_skill": "MLOps",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1196,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Lineage and Metadata",
          "id": 28,
          "rationale": "Cataloging, documenting, and tracing how data moves and changes across systems. This dimension supports impact analysis, governance, discoverability, and operational understanding of datasets.",
          "slug": "data-lineage-and-metadata",
          "source": "db"
        },
        "dimension_id": 28,
        "input_skill": "MLOps",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1196,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Deployment Rollouts and Release Control",
          "id": 51,
          "rationale": "Practices for safely promoting models through environments and managing rollback when production behavior changes. This dimension covers release gating, version pinning, and rollout strategies specific to ML systems.",
          "slug": "deployment-rollouts-and-release-control",
          "source": "db"
        },
        "dimension_id": 51,
        "input_skill": "MLOps",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1196,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "MLOps Platforms and Lifecycle",
          "id": 43,
          "rationale": "End-to-end managed platforms used to train, deploy, register, and govern models across their lifecycle. This is the operational control plane for production ML workflows.",
          "slug": "mlops-platforms-and-lifecycle",
          "source": "db"
        },
        "dimension_id": 43,
        "input_skill": "MLflow",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 214,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "MLOps Platforms and Lifecycle",
          "id": 43,
          "rationale": "End-to-end managed platforms used to train, deploy, register, and govern models across their lifecycle. This is the operational control plane for production ML workflows.",
          "slug": "mlops-platforms-and-lifecycle",
          "source": "db"
        },
        "dimension_id": 43,
        "input_skill": "Kubeflow",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 213,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Containerization and Image Builds",
          "id": 152,
          "rationale": "Container image creation, tagging, hardening, and registry workflows used to package services for deployment. This is coherent because DevOps often owns the build-to-image path that feeds runtime environments.",
          "slug": "containerization-and-image-builds",
          "source": "db"
        },
        "dimension_id": 152,
        "input_skill": "Docker",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 61,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 3,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Deployment and Cloud Platforms",
          "id": 418,
          "rationale": "Platform-as-a-Service and container environments for deploying Ruby applications.",
          "slug": "deployment-and-cloud-platforms",
          "source": "db"
        },
        "dimension_id": 418,
        "input_skill": "Docker",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
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