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Pipeline run

e5e6842a-9a1e-457e-9159-d70fb220cbf8

Pipeline LLM cost (USD)
API 1: $0.0037 API 2: $0.0001 API 3: $0.0000 Total: $0.0038

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Integration and event handling
Build backend and data-processing services for AI-driven price optimization at massive scale, including third-party API integrations, data prep for ML models, and serverless/containerized microservices. You’ll write Python/SQL scripts and backend code to process huge daily volumes and support production deployments.
"Develop API based integrations with third party tech platforms"
Tech stack maturity
Modern Cloud Native
The stack centers on Python/Django with Docker, Kubernetes, microservices, Redis, SQL/NoSQL, and AI/ML capabilities, which aligns with a modern cloud-native backend environment.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.70 / 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): AI, ML, Machine Learning, Artificial Intelligence
Evidence — skills matched in JD (15)
Python Django SQL Docker Kubernetes Redis Agile Serverless Microservices NoSQL Artificial Intelligence Machine Learning API SaaS Containerization
Skill cluster (9 dimension groups, role-scoped)
AI Governance and Model Security
Machine Learning
Caching and State Management
Redis
Container Orchestration Platforms
Kubernetes
Deployment and Runtime Configuration
Docker
Microservices and Distributed Systems
Microservices
NoSQL Databases
NoSQL
Programming Languages
Python
Web Application Frameworks
Django
Cross-cutting / unaligned
SQL Agile Serverless Artificial Intelligence API SaaS Containerization
Show KRA description ↓
The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to: Backend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day). Integrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc.) Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s). AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale. Distributed cloud architecture: Apply serverless and container based technologies in a micro-services environment to develop highly scalable backend codes. Agile development: Follow agile development processes to achieve impactful outcomes. Entrepreneurial mind set with a positive attitude is a must. Prior experience (minimum 2 years) in backend development. Expert knowledge of new generation technologies is a must (e.g. Machine Queues, MSA architecture, PWA architecture, No-SQL, Serverless, Redis, Python, Django, SQL, Docker/Containers/Kubernetes, etc.). Strong acumen in algorithmic problem solving. Self-learner: highly curious, self-starter and can work with minimum supervision and guidance. Track record of excellence in academics or non-academic areas, with significant accomplishments. Excellent written & oral communication and inter-personal skills, with high degree of comfort working in teams and making teams successful.

Signals

Skill backend-engineer
0.40
Alias backend-engineer
1.00
KRA data-engineer
0.53

Post-classification

Centroidupdated · n=1021
Alias collision log
New-role queue
New skills captured3
New KRA capturedyes

Captured for admin review

Serverless primary Backend Developer pending
SaaS primary Backend Developer pending
Containerization primary Backend Developer pending
R&R fragment (sim 0.00) Backend Developer pending

The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optim…

Status: completed Created: 2026-05-27T15:37:26.346227Z Updated: 2026-06-12T16:11:34.263058Z API 3 duration: 27812 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

Backend Developer

CASE A

slug: backend-engineer · id: 1 · source: db

Exact alias hit on backend-engineer (1.0) — no other alias at this confidence; skill_top backend-engineer 0.40 does not contradict

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
1
Skipped

Job description

Job Description

The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to:

Backend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).
Integrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc.)
Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).
AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.
Distributed cloud architecture: Apply serverless and container based technologies in a micro-services environment to develop highly scalable backend codes.
Agile development: Follow agile development processes to achieve impactful outcomes.


Candidate Profile

Entrepreneurial mind set with a positive attitude is a must.
Prior experience (minimum 2 years) in backend development.
Expert knowledge of new generation technologies is a must (e.g. Machine Queues, MSA architecture, PWA architecture, No-SQL, Serverless, Redis, Python, Django, SQL, Docker/Containers/Kubernetes, etc.).
Strong acumen in algorithmic problem solving.
Self-learner: highly curious, self-starter and can work with minimum supervision and guidance.
Track record of excellence in academics or non-academic areas, with significant accomplishments.
Excellent written & oral communication and inter-personal skills, with high degree of comfort working in teams and making teams successful.


Qualifications

BTech / BE / BS / MTech / MCA / ME / MS in Computer Science/Engineering, IT or related field
2 - 5 years work experience.


(ref:hirist.com)

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 saved
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 skipped (dimension not under chosen role)
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)
Django Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Django id=9 · django

Aliases — catalog

  • Django (CANONICAL) primary
  • Django 1 (VERSION)
  • Django 1.x (VERSION)
  • Django 2 (VERSION)
  • Django 2.x (VERSION)
  • Django 3 (VERSION)
  • Django 3.x (VERSION)
  • Django 4 (VERSION)
  • Django 4.x (VERSION)
  • Django 5 (VERSION)
  • Django 5.x (VERSION)
  • Django1 (VERSION)
  • Django2 (VERSION)
  • Django3 (VERSION)
  • Django4 (VERSION)
  • Django5 (VERSION)
  • django 2 (VERSION)
  • django 2.x (VERSION)
  • django 3 (VERSION)
  • django 3.x (VERSION)
  • django 4 (VERSION)
  • django 4.x (VERSION)
  • django 5 (VERSION)
  • django 5.0 (VERSION)
  • django 5.x (VERSION)
  • django2 (VERSION)
  • django2.x (VERSION)
  • django3 (VERSION)
  • django3.x (VERSION)
  • django4 (VERSION)
  • django4.x (VERSION)
  • django5 (VERSION)
  • django5.0 (VERSION)
  • django5.x (VERSION)

Context tags (catalog)

Celery Django REST Framework Django Signals Jinja2 MVT ORM PostgreSQL QuerySet REST URL routing admin interface admin site authentication celery csrf deployment forms gunicorn middleware migrations models pytest querysets settings signals static files templates views

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Web Framework
Vendor
Django Software Foundation
License
bsd
Year introduced
2005
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
5

Maturity reasoning: Django appears in many backend web job descriptions and remains a standard Python web framework; its GitHub ecosystem and long-term LTS releases show sustained market demand.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
35
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Frameworks & Libraries Catalog dimension db id 360

    Library dimension (catalog)

    Roles linked in library: Drupal Dev, Engineering Manager

  • Web Application Frameworks Catalog dimension db id 2

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer, Java Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Frameworks & Libraries
frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Web Application Frameworks
web-application-frameworks
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)
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 saved
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 skipped (dimension not under chosen role)
Redis Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Redis id=31 · redis

Aliases — catalog

  • Redis (CANONICAL) primary

Context tags (catalog)

JSON serialization JSON support LRU eviction Lua scripting Redis Cluster Redis Sentinel Redis Streams TTL backup and restore cache connection pooling data persistence hashes in-memory key expiration lists performance tuning persistence pipeline pub/sub replication sentinel sharding sorted sets streams transactions

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Key Value Store
Vendor
Redis Labs
License
apache_2
Year introduced
2009
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: Redis appears in many job descriptions for caching, queues, and session storage, and is a standard datastore in modern backend stacks; vendor activity and broad ecosystem support indicate strong market demand.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
28
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Caching and State Management Catalog dimension db id 7

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer

  • Magento Caching and Performance Catalog dimension db id 404

    Library dimension (catalog)

    Roles linked in library: Magento Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Caching and State Management
caching-and-state-management
Existing dimension (library) · Role↔dimension saved
Magento Caching and Performance
magento-caching-and-performance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Agile id=520 · agile

Aliases — catalog

  • Agile (CANONICAL) primary

Context tags (catalog)

Kanban SAFe Scrum backlog backlog grooming burndown burndown chart continuous delivery continuous improvement cross-functional daily standup epics incremental development iteration iteration planning lean product backlog product owner retrospective sprint sprint planning stand-up story points user stories velocity

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Agile
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3594
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Software Concepts, Patterns & Practices Catalog dimension db id 478

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

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)
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Serverless Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Serverless Framework id=800 · serverless-framework

Aliases — catalog

  • Serverless Framework (CANONICAL) primary

Context tags (catalog)

API Gateway AWS Lambda CI/CD CloudFormation DynamoDB IAM roles S3 SAM Step Functions YAML cold start deployment stages event-driven microservices serverless.yml

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Infrastructure As Code Framework
Vendor
Serverless, Inc.
License
mit
Year introduced
2015
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: Commonly listed in cloud/IaC job descriptions for AWS Lambda deployments; strong GitHub usage and vendor ecosystem support indicate broad adoption, though often alongside newer tools like SST/CDK.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
145
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Infrastructure as Code Catalog dimension db id 132

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Infrastructure as Code
infrastructure-as-code
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Microservices Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: microservices id=41 · microservices

Aliases — catalog

  • microservices (CANONICAL) primary

Context tags (catalog)

API Gateway API gateway CQRS DevOps Docker Kubernetes REST API RESTful services Saga pattern Spring Boot circuit breaker containerization decentralized distributed tracing domain-driven design event sourcing event-driven event-driven architecture gRPC load balancing message broker microservices patterns monitoring scalability service discovery service mesh

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Distributed System Architecture
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Microservices is a common architecture in job descriptions across backend/cloud roles, and major vendors like AWS, Google Cloud, and Kubernetes ecosystems provide first-class support and reference patterns.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
1
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Microservices and Distributed Systems Catalog dimension db id 9

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Node.js Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension saved
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 saved
Artificial Intelligence Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Artificial Intelligence id=1357 · artificial-intelligence

Aliases — catalog

  • Artificial Intelligence (CANONICAL)

Context tags (catalog)

AI ethics PyTorch TensorFlow algorithm optimization computer vision data mining deep learning machine learning model training natural language processing neural networks predictive analytics reinforcement learning supervised learning unsupervised learning

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Artificial Intelligence
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: AI appears in a large and growing share of job descriptions across software, data, and product roles, and major vendors (Microsoft, Google, AWS) have standardized AI offerings, signaling broad market adoption.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1020
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)
Machine Learning Primary 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 skipped (dimension not under chosen role)
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
API Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: API id=1568 · api

Aliases — catalog

  • API (CANONICAL)

Context tags (catalog)

API gateway GraphQL JSON OAuth REST SDK SOAP XML authentication endpoint microservices rate limiting throttling versioning webhooks

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Application Programming Interface
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: APIs are a core requirement in most software engineering JDs and underpin common integrations across cloud, mobile, and web stacks; major vendors like AWS, Stripe, and Google Cloud center products on API-first usage.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1174
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • API Integration and Data Fetching Catalog dimension db id 127

    Library dimension (catalog)

    Roles linked in library: Angular Frontend Developer, Frontend Developer, Fullstack Developer, Fullstack Developer, React Frontend Developer, Svelte Frontend Developer, Vue Frontend Developer, Web Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
API Integration and Data Fetching
api-integration-and-data-fetching
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SaaS Primary 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
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Containerization Primary 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
DevOps Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED

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 saved
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 skipped (dimension not under chosen role)
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)
Django in_db
Frameworks & Libraries
frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Django in_db
Web Application Frameworks
web-application-frameworks
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)
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 saved
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 skipped (dimension not under chosen role)
Redis in_db
Caching and State Management
caching-and-state-management
Existing dimension (library) · Role↔dimension saved
Redis in_db
Magento Caching and Performance
magento-caching-and-performance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Serverless new
Infrastructure as Code
infrastructure-as-code
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Microservices in_db
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension saved
NoSQL in_db
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension saved
Artificial Intelligence in_db
React Frontend Development
d_init_01
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 skipped (dimension not under chosen role)
Machine Learning in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
API in_db
API Integration and Data Fetching
api-integration-and-data-fetching
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed SaaS | type=Cloud Platforms subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Containerization | type=DevOps Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
dimension_skill_link_proposed Serverless ↔ Infrastructure as Code
nano JD Parser — gpt-4.1-nano click to toggle
RoleBackend Developer
Experience2 - 5 years work experience
DomainSoftware & SaaS Products
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "SaaS",
        "Software Products"
      ],
      "domain": "Software \u0026 SaaS Products"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE/BSC - Computer Science/Engineering (or related)",
      "raw": "BTech / BE / BS / MTech / MCA / ME / MS in Computer Science/Engineering, IT or related field",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": 5,
    "min": 2,
    "raw": "2 - 5 years work experience"
  },
  "job_locations": [],
  "role": "Backend Developer",
  "role_aliases": [
    "Software Engineer",
    "Backend Engineer",
    "SDE"
  ],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 6,
      "heading": "Job Description",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "The primary role of the",
        "last_5_words": "achieve impactful outcomes."
      },
      "text": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to:\n\nBackend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).\nIntegrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc.)\nData engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).\nAI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.\nDistributed cloud architecture: Apply serverless and container based technologies in a micro-services environment to develop highly scalable backend codes.\nAgile development: Follow agile development processes to achieve impactful outcomes.",
      "word_count": 174
    },
    {
      "bullet_count": 7,
      "heading": "Candidate Profile",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Entrepreneurial mind set with",
        "last_5_words": "making teams successful."
      },
      "text": "Entrepreneurial mind set with a positive attitude is a must.\nPrior experience (minimum 2 years) in backend development.\nExpert knowledge of new generation technologies is a must (e.g. Machine Queues, MSA architecture, PWA architecture, No-SQL, Serverless, Redis, Python, Django, SQL, Docker/Containers/Kubernetes, etc.).\nStrong acumen in algorithmic problem solving.\nSelf-learner: highly curious, self-starter and can work with minimum supervision and guidance.\nTrack record of excellence in academics or non-academic areas, with significant accomplishments.\nExcellent written \u0026 oral communication and inter-personal skills, with high degree of comfort working in teams and making teams successful.",
      "word_count": 104
    }
  ],
  "urls": [
    {
      "type": "other",
      "url": "https://hirist.com"
    }
  ]
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "Django"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "Docker"
    },
    {
      "is_primary": true,
      "skill_name": "Kubernetes"
    },
    {
      "is_primary": true,
      "skill_name": "Redis"
    },
    {
      "is_primary": true,
      "skill_name": "Agile"
    },
    {
      "is_primary": true,
      "skill_name": "Serverless"
    },
    {
      "is_primary": true,
      "skill_name": "Microservices"
    },
    {
      "is_primary": true,
      "skill_name": "NoSQL"
    },
    {
      "is_primary": true,
      "skill_name": "Artificial Intelligence"
    },
    {
      "is_primary": true,
      "skill_name": "Machine Learning"
    },
    {
      "is_primary": true,
      "skill_name": "API"
    },
    {
      "is_primary": true,
      "skill_name": "SaaS"
    },
    {
      "is_primary": true,
      "skill_name": "Containerization"
    }
  ],
  "jd_role": {
    "display_name": "Backend Developer",
    "rationale": null,
    "role_aliases": [
      "Software Engineer",
      "Backend Engineer",
      "SDE"
    ],
    "role_archetype": "Engineering",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": null,
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "SaaS",
          "Software Products"
        ],
        "domain": "Software \u0026 SaaS Products"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "BTECH/BE/BSC - Computer Science/Engineering (or related)",
        "raw": "BTech / BE / BS / MTech / MCA / ME / MS in Computer Science/Engineering, IT or related field",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": 5,
      "min": 2,
      "raw": "2 - 5 years work experience"
    },
    "job_locations": [],
    "role": "Backend Developer",
    "role_aliases": [
      "Software Engineer",
      "Backend Engineer",
      "SDE"
    ],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 6,
        "heading": "Job Description",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "The primary role of the",
          "last_5_words": "achieve impactful outcomes."
        },
        "text": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to:\n\nBackend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).\nIntegrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc.)\nData engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).\nAI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.\nDistributed cloud architecture: Apply serverless and container based technologies in a micro-services environment to develop highly scalable backend codes.\nAgile development: Follow agile development processes to achieve impactful outcomes.",
        "word_count": 174
      },
      {
        "bullet_count": 7,
        "heading": "Candidate Profile",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Entrepreneurial mind set with",
          "last_5_words": "making teams successful."
        },
        "text": "Entrepreneurial mind set with a positive attitude is a must.\nPrior experience (minimum 2 years) in backend development.\nExpert knowledge of new generation technologies is a must (e.g. Machine Queues, MSA architecture, PWA architecture, No-SQL, Serverless, Redis, Python, Django, SQL, Docker/Containers/Kubernetes, etc.).\nStrong acumen in algorithmic problem solving.\nSelf-learner: highly curious, self-starter and can work with minimum supervision and guidance.\nTrack record of excellence in academics or non-academic areas, with significant accomplishments.\nExcellent written \u0026 oral communication and inter-personal skills, with high degree of comfort working in teams and making teams successful.",
        "word_count": 104
      }
    ],
    "urls": [
      {
        "type": "other",
        "url": "https://hirist.com"
      }
    ]
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "e5e6842a-9a1e-457e-9159-d70fb220cbf8",
  "stage3_signals": {
    "alias_found": true,
    "alias_match_roles": [
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": null,
        "matched_skills": null,
        "role_id": 1,
        "score": 1.0,
        "slug": "backend-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).",
            "similarity": 0.5885
          },
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.",
            "similarity": 0.5457
          },
          {
            "kra_text": "Builds data ingestion pipelines to collect data from transactional databases, third-party APIs, event streams, and file sources into centralized data platforms.",
            "sentence": "Integrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc. )",
            "similarity": 0.462
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.5321,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Engineer",
        "kra_matches": [
          {
            "kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
            "sentence": "Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).",
            "similarity": 0.5704
          },
          {
            "kra_text": "Integrates AI model API responses with application business logic, database writes, event publishing, and downstream service orchestration.",
            "sentence": "AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.",
            "similarity": 0.5157
          },
          {
            "kra_text": "Integrates AI model API responses with application business logic, database writes, event publishing, and downstream service orchestration.",
            "sentence": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to:",
            "similarity": 0.5039
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 13,
        "score": 0.53,
        "slug": "ai-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": [
          {
            "kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
            "sentence": "Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).",
            "similarity": 0.5614
          },
          {
            "kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
            "sentence": "AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.",
            "similarity": 0.5155
          },
          {
            "kra_text": "Builds model serving infrastructure to deploy trained models as real-time prediction APIs or batch inference jobs using TorchServe, TensorFlow Serving, or SageMaker.",
            "sentence": "Backend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).",
            "similarity": 0.4731
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 3,
        "score": 0.5167,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Compliance Officer",
        "kra_matches": [
          {
            "kra_text": "Reviews AI use cases and model deployments against applicable regulations, internal ethics policies, and governance guidelines prior to production approval.",
            "sentence": "AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.",
            "similarity": 0.545
          },
          {
            "kra_text": "Maps AI system behaviors and data processing activities to regulatory requirements including EU AI Act, GDPR, CCPA, and sector-specific compliance frameworks.",
            "sentence": "Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).",
            "similarity": 0.5291
          },
          {
            "kra_text": "Maps AI system behaviors and data processing activities to regulatory requirements including EU AI Act, GDPR, CCPA, and sector-specific compliance frameworks.",
            "sentence": "Backend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).",
            "similarity": 0.4512
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 12,
        "score": 0.5084,
        "slug": "ai-compliance-officer",
        "total_count": null
      },
      {
        "display_name": "React Native Developer",
        "kra_matches": [
          {
            "kra_text": "integrate backend APIs",
            "sentence": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to:",
            "similarity": 0.5393
          },
          {
            "kra_text": "integrate backend APIs",
            "sentence": "Integrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc. )",
            "similarity": 0.5077
          },
          {
            "kra_text": "integrate backend APIs",
            "sentence": "Backend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).",
            "similarity": 0.4722
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 73,
        "score": 0.5064,
        "slug": "react-native-developer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 6,
        "matched_skills": [
          "Django",
          "Docker",
          "NoSQL",
          "Python",
          "Redis",
          "microservices"
        ],
        "role_id": 1,
        "score": 0.4,
        "slug": "backend-engineer",
        "total_count": 15
      },
      {
        "display_name": "Engineering Manager",
        "kra_matches": null,
        "matched_count": 4,
        "matched_skills": [
          "Agile",
          "Django",
          "Python",
          "SQL"
        ],
        "role_id": 121,
        "score": 0.2667,
        "slug": "engineering-manager",
        "total_count": 15
      },
      {
        "display_name": "Fullstack Developer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "API",
          "Django",
          "Python"
        ],
        "role_id": 15,
        "score": 0.2,
        "slug": "full-stack-engineer",
        "total_count": 15
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "Kubernetes",
          "Machine Learning",
          "Python"
        ],
        "role_id": 3,
        "score": 0.2,
        "slug": "ml-engineer",
        "total_count": 15
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "Kubernetes",
          "Machine Learning",
          "Python"
        ],
        "role_id": 16,
        "score": 0.2,
        "slug": "ml-ops-engineer",
        "total_count": 15
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "A",
    "chosen_role": {
      "display_name": "Backend Developer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 1,
      "score": 1.0,
      "slug": "backend-engineer",
      "total_count": null
    },
    "confidence": 1.0,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [],
    "matched_kras": [],
    "matched_skills": [],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top backend-engineer 0.40 does not contradict",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 1021,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": {
      "best_kra_similarity": 0.0,
      "queue_id": 1075,
      "r_and_r_preview": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optim",
      "role_display_name": "Backend Developer",
      "role_slug": "backend-engineer",
      "status": "pending"
    },
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 15391,
        "role_display_name": "Backend Developer",
        "role_slug": "backend-engineer",
        "skill_name": "Serverless",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 15392,
        "role_display_name": "Backend Developer",
        "role_slug": "backend-engineer",
        "skill_name": "SaaS",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 15393,
        "role_display_name": "Backend Developer",
        "role_slug": "backend-engineer",
        "skill_name": "Containerization",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
  "alias_matches": [
    {
      "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": 82,
      "existing_alias_text": "Django",
      "input_term": "Django",
      "matched_canonical": {
        "category_id": 5,
        "display_name": "Django",
        "id": 9,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "django",
        "sub_category_id": 35,
        "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": {
        "category_id": 6,
        "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"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 198,
      "existing_alias_text": "Docker",
      "input_term": "Docker",
      "matched_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"
      },
      "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": 168,
      "existing_alias_text": "Redis",
      "input_term": "Redis",
      "matched_canonical": {
        "category_id": 3,
        "display_name": "Redis",
        "id": 31,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "redis",
        "sub_category_id": 28,
        "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": 868,
      "existing_alias_text": "Agile",
      "input_term": "Agile",
      "matched_canonical": {
        "category_id": 8,
        "display_name": "Agile",
        "id": 520,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "agile",
        "sub_category_id": 3594,
        "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": 1345,
      "existing_alias_text": "Serverless Framework",
      "input_term": "Serverless",
      "matched_canonical": {
        "category_id": 5,
        "display_name": "Serverless Framework",
        "id": 800,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "serverless-framework",
        "sub_category_id": 145,
        "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": 178,
      "existing_alias_text": "microservices",
      "input_term": "Microservices",
      "matched_canonical": {
        "category_id": 1,
        "display_name": "microservices",
        "id": 41,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
        "slug": "microservices",
        "sub_category_id": 1,
        "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": 1989,
      "existing_alias_text": "NoSQL",
      "input_term": "NoSQL",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "NoSQL",
        "id": 1346,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "nosql",
        "sub_category_id": 1019,
        "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": 2016,
      "existing_alias_text": "Artificial Intelligence",
      "input_term": "Artificial Intelligence",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "Artificial Intelligence",
        "id": 1357,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "artificial-intelligence",
        "sub_category_id": 1020,
        "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": 2015,
      "existing_alias_text": "Machine Learning",
      "input_term": "Machine Learning",
      "matched_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"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 2514,
      "existing_alias_text": "API",
      "input_term": "API",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "API",
        "id": 1568,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "api",
        "sub_category_id": 1174,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    }
  ],
  "candidate_roles": [
    {
      "display_name": "Cloud Security Engineer",
      "id": 23,
      "rationale": null,
      "role_archetype": null,
      "slug": "cloud-security-engineer",
      "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": "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"
    },
    {
      "display_name": "Engineering Manager",
      "id": 121,
      "rationale": null,
      "role_archetype": null,
      "slug": "engineering-manager",
      "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": "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": "AR/VR Engineer",
      "id": 8,
      "rationale": null,
      "role_archetype": null,
      "slug": "ar-vr-engineer",
      "source": "db"
    },
    {
      "display_name": "Python Backend Developer",
      "id": 80,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "python-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Drupal Dev",
      "id": 228,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "drupal-dev",
      "source": "db"
    },
    {
      "display_name": "Java Backend Developer",
      "id": 79,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "java-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Node.js Backend Developer",
      "id": 82,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "node-backend-developer",
      "source": "db"
    },
    {
      "display_name": "PHP Backend Developer",
      "id": 86,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "php-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Pega Developer",
      "id": 24,
      "rationale": null,
      "role_archetype": null,
      "slug": "pega-developer",
      "source": "db"
    },
    {
      "display_name": "DevOps Engineer",
      "id": 10,
      "rationale": null,
      "role_archetype": null,
      "slug": "devops-engineer",
      "source": "db"
    },
    {
      "display_name": "Ruby Backend Developer",
      "id": 85,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "ruby-backend-developer",
      "source": "db"
    },
    {
      "display_name": ".NET Backend Developer",
      "id": 83,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "dotnet-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Go Backend Developer",
      "id": 81,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "go-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Cloud Architect",
      "id": 9,
      "rationale": null,
      "role_archetype": null,
      "slug": "cloud-architect",
      "source": "db"
    },
    {
      "display_name": "Kotlin Backend Developer",
      "id": 84,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "kotlin-server-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Scala Backend Developer",
      "id": 87,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "scala-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Magento Dev",
      "id": 231,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "magento-dev",
      "source": "db"
    },
    {
      "display_name": "AI Engineer",
      "id": 13,
      "rationale": null,
      "role_archetype": null,
      "slug": "ai-engineer",
      "source": "db"
    },
    {
      "display_name": "Angular Frontend Developer",
      "id": 90,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "angular-frontend-developer",
      "source": "db"
    },
    {
      "display_name": "Frontend Developer",
      "id": 7,
      "rationale": null,
      "role_archetype": null,
      "slug": "frontend-engineer",
      "source": "db"
    },
    {
      "display_name": "React Frontend Developer",
      "id": 89,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "react-frontend-developer",
      "source": "db"
    },
    {
      "display_name": "Svelte Frontend Developer",
      "id": 92,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "svelte-frontend-developer",
      "source": "db"
    },
    {
      "display_name": "Vue Frontend Developer",
      "id": 91,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "vue-frontend-developer",
      "source": "db"
    },
    {
      "display_name": "Web Developer",
      "id": 25,
      "rationale": null,
      "role_archetype": null,
      "slug": "web-developer",
      "source": "db"
    }
  ],
  "chosen_role": {
    "display_name": "Backend Developer",
    "id": 1,
    "rationale": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top backend-engineer 0.40 does not contradict",
    "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"
  },
  "dimensions": [
    {
      "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"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Security Engineer",
          "id": 23,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        }
      ]
    },
    {
      "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"
      },
      "input_skill": "Python",
      "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"
        },
        {
          "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"
        }
      ]
    },
    {
      "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": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
          "id": 121,
          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
          "source": "db"
        }
      ]
    },
    {
      "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"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_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": "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": "Python",
      "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": "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"
      },
      "input_skill": "Python",
      "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": "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"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "AR/VR Engineer",
          "id": 8,
          "rationale": null,
          "role_archetype": null,
          "slug": "ar-vr-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Python Programming",
        "id": 290,
        "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
        "slug": "python-programming",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Python Backend Developer",
          "id": 80,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Frameworks \u0026 Libraries",
        "id": 360,
        "rationale": "Manage adoption, integration, and best practices around key software frameworks and libraries.",
        "slug": "frameworks-libraries",
        "source": "db"
      },
      "input_skill": "Django",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Drupal Dev",
          "id": 228,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "drupal-dev",
          "source": "db"
        },
        {
          "display_name": "Engineering Manager",
          "id": 121,
          "rationale": null,
          "role_archetype": null,
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      "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": "SaaS",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Cloud Platforms",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "saas",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Containerization",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "DevOps Tools",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "containerization",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "SaaS",
    "Containerization"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Backend Developer",
    "id": 1,
    "rationale": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top backend-engineer 0.40 does not contradict",
    "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"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Django",
      "tag": "in_db"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Docker",
      "tag": "in_db"
    },
    {
      "skill": "Kubernetes",
      "tag": "in_db"
    },
    {
      "skill": "Redis",
      "tag": "in_db"
    },
    {
      "skill": "Agile",
      "tag": "in_db"
    },
    {
      "skill": "Serverless",
      "tag": "in_db"
    },
    {
      "skill": "Microservices",
      "tag": "in_db"
    },
    {
      "skill": "NoSQL",
      "tag": "in_db"
    },
    {
      "skill": "Artificial Intelligence",
      "tag": "in_db"
    },
    {
      "skill": "Machine Learning",
      "tag": "in_db"
    },
    {
      "skill": "API",
      "tag": "in_db"
    },
    {
      "skill": "SaaS",
      "tag": "new"
    },
    {
      "skill": "Containerization",
      "tag": "new"
    }
  ],
  "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": 1,
        "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": 1,
        "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": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "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": 1,
        "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": 1,
        "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": 1,
        "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": 1,
        "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": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "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": 1,
        "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,
            "slug": "ar-vr-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Python Programming",
          "id": 290,
          "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
          "slug": "python-programming",
          "source": "db"
        },
        "dimension_id": 290,
        "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": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Frameworks \u0026 Libraries",
          "id": 360,
          "rationale": "Manage adoption, integration, and best practices around key software frameworks and libraries.",
          "slug": "frameworks-libraries",
          "source": "db"
        },
        "dimension_id": 360,
        "input_skill": "Django",
        "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": "Drupal Dev",
            "id": 228,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "drupal-dev",
            "source": "db"
          },
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 9,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Web Application Frameworks",
          "id": 2,
          "rationale": "Server frameworks and runtimes used to build HTTP services, controllers, middleware, and request pipelines. These frameworks shape how backend endpoints are structured and delivered.",
          "slug": "web-application-frameworks",
          "source": "db"
        },
        "dimension_id": 2,
        "input_skill": "Django",
        "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": "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"
          },
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "PHP Backend Developer",
            "id": 86,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 9,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "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": 1,
        "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": 1,
        "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": 1,
        "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": 1,
        "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,
        "roles_from_db": [
          {
            "display_name": "Ruby Backend Developer",
            "id": 85,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "ruby-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 61,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "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"
        },
        "dimension_id": 13,
        "input_skill": "Docker",
        "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"
          },
          {
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            "source": "db"
          },
          {
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
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        "skipped_reason": null
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      {
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          "rationale": "Platforms that schedule and manage containerized workloads across clusters and environments. Cloud Architects need these to define workload placement standards, cluster boundaries, and platform capabilities.",
          "slug": "container-orchestration-platforms",
          "source": "db"
        },
        "dimension_id": 134,
        "input_skill": "Kubernetes",
        "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 Architect",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
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            "rationale": null,
            "role_archetype": null,
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        ],
        "skill_dimension_saved": true,
        "skill_id": 726,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
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          "rationale": "Kubernetes-native components used to schedule, accelerate, and isolate ML training and serving workloads. This includes GPU enablement and ML-specific controllers rather than generic cluster administration.",
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          "source": "db"
        },
        "dimension_id": 47,
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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": [
          {
            "display_name": "ML Engineer",
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          {
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            "source": "db"
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        ],
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        "skipped_reason": null
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      {
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          "rationale": "Techniques and systems for reducing latency and managing ephemeral backend state. Covers cache-aside patterns, distributed caches, session stores, and invalidation strategies.",
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          "source": "db"
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        "input_skill": "Redis",
        "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",
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          },
          {
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            "source": "db"
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        ],
        "skill_dimension_saved": true,
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        "skipped_reason": null
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        },
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          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
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        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 520,
        "skill_tag": "in_db",
        "skipped_reason": null
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      {
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          "source": "db"
        },
        "dimension_id": 478,
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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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        ],
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        "dimension_id": 132,
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        "roles_from_db": [
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        ],
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      {
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          "source": "db"
        },
        "dimension_id": 9,
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        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
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          },
          {
            "display_name": "Node.js Backend Developer",
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          },
          {
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        ],
        "skill_dimension_saved": true,
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        "skipped_reason": null
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      {
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          "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": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
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        ],
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        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
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      {
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        "roles_from_db": [
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          {
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            "slug": "ml-ops-engineer",
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        ],
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        },
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        "roles_from_db": [
          {
            "display_name": "Angular Frontend Developer",
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          {
            "display_name": "Fullstack Developer",
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          },
          {
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          },
          {
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          },
          {
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          {
            "display_name": "Vue Frontend Developer",
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            "source": "db"
          },
          {
            "display_name": "Web Developer",
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            "slug": "web-developer",
            "source": "db"
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        ],
        "skill_dimension_saved": true,
        "skill_id": 1568,
        "skill_tag": "in_db",
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      }
    ],
    "new_skills_created": 0,
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    "skill_dimension_saved": 0,
    "skipped": 1
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}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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