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Pipeline run

0298c5ad-96d3-457d-8d1c-ad9b8431a7a3

Pipeline LLM cost (USD)
API 1: $0.0079 API 2: $0.0002 API 3: $0.0000 Total: $0.0081

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · GenAI service development
Build and improve GenAI services in Python, integrating them into the product, tuning performance, and keeping the code modular, reusable, and maintainable. Also work with other teams, deploy via cloud/container tools, and mentor engineers on code quality.
"Contribute to the development of GenAI services that are integral to our product offerings and user experiences."
Tech stack maturity
Modern Cloud Native
An LLM/GenAI Engineer working primarily in Python typically operates in a cloud-first, API-driven, and rapidly evolving ecosystem centered on modern AI services and tooling.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
3.20 / 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, GenAI
Evidence — skills matched in JD (10)
GenAI Python AWS Azure GCP Docker Kubernetes Containerization Orchestration Open Source
Skill cluster (7 dimension groups, role-scoped)
Cloud Platforms & Managed Services
Azure
Cloud Platforms for AI Deployment
GCP
Cloud Provider Platforms
AWS
Containerization and Image Builds
Docker
Kubernetes for ML Workloads
Kubernetes
Python Programming
Python
Cross-cutting / unaligned
GenAI Containerization Orchestration Open Source
Show KRA description ↓
• Contribute to the development of GenAI services that are integral to our product offerings and user experiences. • Implement coding best practices to foster code modularity, reusability, and maintainability, enabling our AI services to remain flexible for future advancements. • Collaborate with cross-functional teams to integrate AI services into the wider product ecosystem, ensuring a smooth developer experience. • Assess and optimize existing AI services to enhance performance and conform to the latest industry trends. • Support and mentor other engineers, contributing to a culture that values technical skill and code quality. • Stay informed on the latest AI technologies and programming techniques, exploring their applicability to our services. • 5+ years of experience in Software Development • Familiarity with GenAI concepts and their implementation • Python • Proven ability to develop scalable, reusable software components and services • Good knowledge of software engineering principles and architectural standards • Experience in working on and contributing to software project teams • Cloud-based development and familiarity with AI-related cloud services (e.g., AWS, Azure, GCP). • Strong communication skills, able to effectively convey technical ideas to varied audiences. • Understanding of containerization and orchestration technologies (e.g., Docker, Kubernetes) for deploying AI services. • Participation in the AI and open-source communities is appreciated.

Signals

Skill data-engineer
0.50
Alias
KRA ai-engineer
0.57

Post-classification

Centroidupdated · n=16
Alias collision log
New-role queue
New skills captured4
New KRA capturedyes

Captured for admin review

GenAI primary LLM / GenAI Engineer pending
Containerization LLM / GenAI Engineer pending
Orchestration LLM / GenAI Engineer pending
Open Source LLM / GenAI Engineer pending
R&R fragment (sim 0.00) LLM / GenAI Engineer pending

• Contribute to the development of GenAI services that are integral to our product offerings and user experiences. • Implement coding best practices to foster code modularity, reusability, and maintai…

Status: completed Created: 2026-05-27T17:39:21.326303Z Updated: 2026-05-27T17:40:19.533897Z API 3 duration: 15250 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

LLM / GenAI Engineer

domain · AI / ML CASE DOMAIN

slug: llm-genai-engineer · id: 151 · source: db

Domain=AI / ML; The JD centers on building and optimizing GenAI services in Python, integrating them into products, and working with cloud and deployment technologies, which best matches an LLM/GenAI engineering role.

Matched skills

GenAIPythonAWSAzureGCPDockerKubernetescloud-based developmentsoftware engineering principlesarchitectural standards

Matched dimensions

GenAI service developmentSoftware component modularity and reusabilityProduct ecosystem integrationAI service performance optimizationCloud-based AI developmentContainerized deployment

Matched KRAs

Contribute to the development of GenAI servicesImplement coding best practicesIntegrate AI services into the wider product ecosystemAssess and optimize existing AI servicesSupport and mentor other engineersStay informed on the latest AI technologies

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

Experience: 5.00 + years

Salary: USD 54000.00 / year (based on experience)

Expected Notice Period: 15 Days

Shift: (GMT+05:30) Asia/Kolkata (IST)

Opportunity Type: Remote

Placement Type: Full Time Contract for 12 Months(40 hrs a week/160 hrs a month)

(*Note: This is a requirement for one of Uplers' client - Andela)

What do you need for this opportunity?

Must have skills required:

GenAI, AWS, Azure, Docker, Kubernetes, Python

Andela is Looking for:

Apply Today and Get Ahead!

By choosing Uplers, you’re not just applying—you’re optimizing your chances of success. Take the fast track to your next career move with Uplers and Andela.

• Exclusive Partnership:



Uplers is the only Indian partner working directly with Andela, giving you unique access to their exclusive roles. This partnership ensures that your application is prioritized and handled with care.

• Direct Connection with Andela Matchers:



By applying through Uplers, you connect directly with Andela Matchers. This direct line of communication speeds up the entire process, ensuring your profile gets the attention it deserves without unnecessary delays.

• Accelerated Application Process:



When you apply through Uplers, your profile is fast-tracked, giving you a significant advantage over other applicants. You’ll skip one of the three assessments required if you apply directly through Andela’s website, saving you time and getting you closer to your dream role faster.

• Streamlined Experience:



Uplers takes the hassle out of the application process, ensuring your journey to joining Andela is smooth and efficient. With our support, you can focus on showcasing your skills and landing the perfect role.

Engagement Type:

• Payout will be managed by Andela
• Job Type : Direct Contract (12 Months) with Andela
• Location: Remote
• No Leave Policy: The number of working days, the talents will work, gets paid accordingly



Key Responsibilities:

• Contribute to the development of GenAI services that are integral to our product offerings and user experiences.
• Implement coding best practices to foster code modularity, reusability, and maintainability, enabling our AI services to remain flexible for future advancements.
• Collaborate with cross-functional teams to integrate AI services into the wider product ecosystem, ensuring a smooth developer experience.
• Assess and optimize existing AI services to enhance performance and conform to the latest industry trends.
• Support and mentor other engineers, contributing to a culture that values technical skill and code quality.
• Stay informed on the latest AI technologies and programming techniques, exploring their applicability to our services.



Must-have skills:

• 5+ years of experience in Software Development
• Familiarity with GenAI concepts and their implementation
• Python
• Proven ability to develop scalable, reusable software components and services
• Good knowledge of software engineering principles and architectural standards
• Experience in working on and contributing to software project teams
• Cloud-based development and familiarity with AI-related cloud services (e.g., AWS, Azure, GCP).
• Strong communication skills, able to effectively convey technical ideas to varied audiences.



Nice-to-have skills:

• Understanding of containerization and orchestration technologies (e.g., Docker, Kubernetes) for deploying AI services.
• Participation in the AI and open-source communities is appreciated.



Overlap: 5+ hours with EST

How to apply for this opportunity?

• Register or login on our portal & fill out the application form.
• Clear the given Video Screening (30 min) and Click on 'Apply' to get shortlisted
• Once it's all done, your profile will be shared with the client for the Interview round.
• When selected, just meet the client and get your exciting career started!



About Uplers:

Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. You will also be assigned to a dedicated Talent Success Coach during the engagement.

(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).

So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Skills from this JD

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

GenAI 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
Machine Learning Frameworks
Sub-category
general
Skill nature
CONCEPT
Volatility
FAST
Typical lifespan
SHORT_LIVED
Version strategy
VERSIONED
Python Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Python id=5 · python

Aliases — catalog

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

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

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

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

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

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension 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)
AWS Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: AWS id=187 · aws

Aliases — catalog

  • AWS (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

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

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

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

  • Vendor Product Families Catalog dimension db id 477

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure id=188 · azure

Aliases — catalog

  • Azure (CANONICAL) primary

Context tags (catalog)

AKS ARM templates App Service Azure AD Azure Active Directory Azure App Service Azure Blob Azure Blob Storage Azure Cognitive Services Azure Cosmos DB Azure DevOps Azure DevTest Labs Azure Functions Azure Kubernetes Service Azure Logic Apps Azure Monitor Azure Networking Azure Resource Manager Azure SQL Azure SQL Database Azure Security Center Azure Storage Azure Storage Explorer Azure Virtual Machines Bicep Blob Storage Cloud Services Cosmos DB Entra ID Functions Infrastructure as Code Key Vault Log Analytics Logic Apps Resource Groups Serverless Computing Service Bus Storage Account Terraform Virtual Machines

Stored enrichment (catalog DB)

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

Maturity reasoning: Azure is broadly adopted and frequently appears in cloud/platform job descriptions alongside AWS and GCP; Microsoft’s ongoing enterprise investment and Azure certification demand signal strong hiring-pipeline relevance.

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

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

  • Cloud Platforms & Managed Services Catalog dimension db id 221

    Library dimension (catalog)

    Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

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

  • Vendor Product Families Catalog dimension db id 477

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GCP Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: GCP id=186 · gcp

Aliases — catalog

  • GCP (CANONICAL) primary

Context tags (catalog)

Anthos App Engine Artifact Registry BigQuery Cloud Build Cloud Composer Cloud Functions Cloud Logging Cloud Monitoring Cloud Run Cloud SQL Cloud Spanner Cloud Storage Compute Engine Dataflow GKE IAM Kubernetes Pub/Sub Service Accounts Stackdriver Terraform VPC

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Google
License
other_open
Year introduced
2011
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: GCP appears frequently in cloud/platform job descriptions and is a major hyperscaler alongside AWS/Azure, with broad enterprise adoption and active vendor investment.

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

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

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Docker id=61 · docker

Aliases — catalog

  • Docker (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Containerization and Image Builds Catalog dimension db id 152

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • Deployment and Cloud Platforms Catalog dimension db id 418

    Library dimension (catalog)

    Roles linked in library: Ruby Backend Developer

  • Deployment and Runtime Configuration Catalog dimension db id 13

    Library dimension (catalog)

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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Containerization and Image Builds
containerization-and-image-builds
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment and Cloud Platforms
deployment-and-cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment and Runtime Configuration
deployment-and-runtime-configuration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kubernetes Secondary 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)
Containerization Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
DevOps Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Orchestration Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Container Orchestration
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Open Source Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: open-source id=1472 · open-source

Aliases — catalog

  • open-source (CANONICAL)

Context tags (catalog)

Apache License GitHub MIT License collaboration community-driven contribution documentation fork issue tracking licensing maintainers pull request repository transparency version control

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Open Source Software Model
Confidence
0.91
Version strategy
NOT_APPLICABLE

Maturity reasoning: Open-source is a standard hiring-pipeline term across software JDs and vendor ecosystems; major cloud, database, and devtool roles routinely require OSS contribution or usage experience.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1111
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
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed

All API 3 persistence rows

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

Skill Tag Dimension Skill↔dim Role↔dim Outcome Notes
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension 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)
AWS in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GCP in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GCP in_db
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GCP in_db
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GCP in_db
Cloud Security Posture Tools
cloud-security-posture-tools
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 skipped (dimension not under chosen role)
Kubernetes in_db
Container Orchestration Platforms
container-orchestration-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kubernetes in_db
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Open Source new
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed GenAI | type=Machine Learning Frameworks subtype=general nature=CONCEPT lifespan=SHORT_LIVED
canonical_skill_proposed Containerization | type=DevOps Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Orchestration | type=Container Orchestration subtype=general nature=CONCEPT lifespan=MULTI_YEAR
dimension_skill_link_proposed Open Source ↔ React Frontend Development
nano JD Parser — gpt-4.1-nano click to toggle
CompanyUplers
Experience5.00 + years
CTC{'max': 54, 'min': 54, 'raw': 'USD 54000.00 / year (based on experience)', 'period': 'annual', 'currency': 'USD'}
DomainOther
Location(remote)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "Our goal is to make",
      "last_5_words": "during the engagement."
    },
    "text": "Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. You will also be assigned to a dedicated Talent Success Coach during the engagement.",
    "word_count": 64
  },
  "archetype_override_applied": true,
  "archetype_override_matched_skills": [
    "Python",
    "Docker",
    "open-source",
    "code quality",
    "GCP",
    "Make",
    "Azure",
    "Kubernetes",
    "Cloud",
    "Role",
    "components",
    "Location",
    "roles",
    "AWS"
  ],
  "certifications": [],
  "company_name": "Uplers",
  "ctc": {
    "currency": "USD",
    "max": 54,
    "min": 54,
    "period": "annual",
    "raw": "USD 54000.00 / year (based on experience)"
  },
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": null,
    "min": 5,
    "raw": "5.00 + years"
  },
  "job_locations": [
    {
      "aliases": [],
      "city": null,
      "country": null,
      "state": null,
      "work_mode": "remote"
    }
  ],
  "role": null,
  "role_aliases": [],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 6,
      "heading": "Key Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Contribute to the development",
        "last_5_words": "their applicability to our services."
      },
      "text": "\u2022 Contribute to the development of GenAI services that are integral to our product offerings and user experiences.\n\u2022 Implement coding best practices to foster code modularity, reusability, and maintainability, enabling our AI services to remain flexible for future advancements.\n\u2022 Collaborate with cross-functional teams to integrate AI services into the wider product ecosystem, ensuring a smooth developer experience.\n\u2022 Assess and optimize existing AI services to enhance performance and conform to the latest industry trends.\n\u2022 Support and mentor other engineers, contributing to a culture that values technical skill and code quality.\n\u2022 Stay informed on the latest AI technologies and programming techniques, exploring their applicability to our services.",
      "word_count": 90
    },
    {
      "bullet_count": 8,
      "heading": "Must-have skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 5+ years of experience in",
        "last_5_words": "to varied audiences."
      },
      "text": "\u2022 5+ years of experience in Software Development\n\u2022 Familiarity with GenAI concepts and their implementation\n\u2022 Python\n\u2022 Proven ability to develop scalable, reusable software components and services\n\u2022 Good knowledge of software engineering principles and architectural standards\n\u2022 Experience in working on and contributing to software project teams\n\u2022 Cloud-based development and familiarity with AI-related cloud services (e.g., AWS, Azure, GCP).\n\u2022 Strong communication skills, able to effectively convey technical ideas to varied audiences.",
      "word_count": 83
    },
    {
      "bullet_count": 2,
      "heading": "Nice-to-have skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Understanding of containerization and",
        "last_5_words": "is appreciated."
      },
      "text": "\u2022 Understanding of containerization and orchestration technologies (e.g., Docker, Kubernetes) for deploying AI services.\n\u2022 Participation in the AI and open-source communities is appreciated.",
      "word_count": 30
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "GenAI"
    },
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": false,
      "skill_name": "AWS"
    },
    {
      "is_primary": false,
      "skill_name": "Azure"
    },
    {
      "is_primary": false,
      "skill_name": "GCP"
    },
    {
      "is_primary": false,
      "skill_name": "Docker"
    },
    {
      "is_primary": false,
      "skill_name": "Kubernetes"
    },
    {
      "is_primary": false,
      "skill_name": "Containerization"
    },
    {
      "is_primary": false,
      "skill_name": "Orchestration"
    },
    {
      "is_primary": false,
      "skill_name": "Open Source"
    }
  ],
  "jd_role": null,
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "Our goal is to make",
        "last_5_words": "during the engagement."
      },
      "text": "Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. You will also be assigned to a dedicated Talent Success Coach during the engagement.",
      "word_count": 64
    },
    "archetype_override_applied": true,
    "archetype_override_matched_skills": [
      "Python",
      "Docker",
      "open-source",
      "code quality",
      "GCP",
      "Make",
      "Azure",
      "Kubernetes",
      "Cloud",
      "Role",
      "components",
      "Location",
      "roles",
      "AWS"
    ],
    "certifications": [],
    "company_name": "Uplers",
    "ctc": {
      "currency": "USD",
      "max": 54,
      "min": 54,
      "period": "annual",
      "raw": "USD 54000.00 / year (based on experience)"
    },
    "domain": {
      "primary": {
        "aliases": [],
        "domain": "Other"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": null,
      "min": 5,
      "raw": "5.00 + years"
    },
    "job_locations": [
      {
        "aliases": [],
        "city": null,
        "country": null,
        "state": null,
        "work_mode": "remote"
      }
    ],
    "role": null,
    "role_aliases": [],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 6,
        "heading": "Key Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Contribute to the development",
          "last_5_words": "their applicability to our services."
        },
        "text": "\u2022 Contribute to the development of GenAI services that are integral to our product offerings and user experiences.\n\u2022 Implement coding best practices to foster code modularity, reusability, and maintainability, enabling our AI services to remain flexible for future advancements.\n\u2022 Collaborate with cross-functional teams to integrate AI services into the wider product ecosystem, ensuring a smooth developer experience.\n\u2022 Assess and optimize existing AI services to enhance performance and conform to the latest industry trends.\n\u2022 Support and mentor other engineers, contributing to a culture that values technical skill and code quality.\n\u2022 Stay informed on the latest AI technologies and programming techniques, exploring their applicability to our services.",
        "word_count": 90
      },
      {
        "bullet_count": 8,
        "heading": "Must-have skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 5+ years of experience in",
          "last_5_words": "to varied audiences."
        },
        "text": "\u2022 5+ years of experience in Software Development\n\u2022 Familiarity with GenAI concepts and their implementation\n\u2022 Python\n\u2022 Proven ability to develop scalable, reusable software components and services\n\u2022 Good knowledge of software engineering principles and architectural standards\n\u2022 Experience in working on and contributing to software project teams\n\u2022 Cloud-based development and familiarity with AI-related cloud services (e.g., AWS, Azure, GCP).\n\u2022 Strong communication skills, able to effectively convey technical ideas to varied audiences.",
        "word_count": 83
      },
      {
        "bullet_count": 2,
        "heading": "Nice-to-have skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Understanding of containerization and",
          "last_5_words": "is appreciated."
        },
        "text": "\u2022 Understanding of containerization and orchestration technologies (e.g., Docker, Kubernetes) for deploying AI services.\n\u2022 Participation in the AI and open-source communities is appreciated.",
        "word_count": 30
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "0298c5ad-96d3-457d-8d1c-ad9b8431a7a3",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "AI Engineer",
        "kra_matches": [
          {
            "kra_text": "Integrates AI model API responses with application business logic, database writes, event publishing, and downstream service orchestration.",
            "sentence": "Collaborate with cross-functional teams to integrate AI services into the wider product ecosystem, ensuring a smooth developer experience.",
            "similarity": 0.6143
          },
          {
            "kra_text": "Optimizes AI pipeline efficiency by tuning model selection, context window usage, prompt caching, and batching strategies to reduce cost and latency.",
            "sentence": "Assess and optimize existing AI services to enhance performance and conform to the latest industry trends.",
            "similarity": 0.5717
          },
          {
            "kra_text": "Translates product requirements into AI-powered features by integrating large language models like GPT-4, Claude, or Gemini into application workflows via API.",
            "sentence": "Contribute to the development of GenAI services that are integral to our product offerings and user experiences.",
            "similarity": 0.5226
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 13,
        "score": 0.5696,
        "slug": "ai-engineer",
        "total_count": null
      },
      {
        "display_name": "DevOps Engineer",
        "kra_matches": [
          {
            "kra_text": "Manages container orchestration with Kubernetes and Docker, deploying applications as pods, managing namespaces, and configuring auto-scaling across cloud environments.",
            "sentence": "Understanding of containerization and orchestration technologies (e.g. , Docker, Kubernetes) for deploying AI services.",
            "similarity": 0.6106
          },
          {
            "kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
            "sentence": "Collaborate with cross-functional teams to integrate AI services into the wider product ecosystem, ensuring a smooth developer experience.",
            "similarity": 0.5337
          },
          {
            "kra_text": "Provisions and manages cloud infrastructure on AWS, Azure, or GCP using Terraform or CloudFormation to enforce infrastructure-as-code standards.",
            "sentence": "Cloud-based development and familiarity with AI-related cloud services (e.g. , AWS, Azure, GCP).",
            "similarity": 0.5124
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 10,
        "score": 0.5522,
        "slug": "devops-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Compliance Officer",
        "kra_matches": [
          {
            "kra_text": "Monitors deployed AI systems for compliance policy drift, regulatory changes, and emerging requirements affecting existing AI deployments.",
            "sentence": "Assess and optimize existing AI services to enhance performance and conform to the latest industry trends.",
            "similarity": 0.6023
          },
          {
            "kra_text": "Defines AI governance frameworks including fairness standards, transparency obligations, explainability requirements, and human oversight accountability structures.",
            "sentence": "Implement coding best practices to foster code modularity, reusability, and maintainability, enabling our AI services to remain flexible for future advancements.",
            "similarity": 0.5245
          },
          {
            "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": "Stay informed on the latest AI technologies and programming techniques, exploring their applicability to our services.",
            "similarity": 0.4979
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 12,
        "score": 0.5416,
        "slug": "ai-compliance-officer",
        "total_count": null
      },
      {
        "display_name": "Flutter Developer",
        "kra_matches": [
          {
            "kra_text": "collaborate with design, product, and backend teams",
            "sentence": "Collaborate with cross-functional teams to integrate AI services into the wider product ecosystem, ensuring a smooth developer experience.",
            "similarity": 0.5904
          },
          {
            "kra_text": "structure reusable application code",
            "sentence": "Proven ability to develop scalable, reusable software components and services",
            "similarity": 0.5354
          },
          {
            "kra_text": "structure reusable application code",
            "sentence": "Implement coding best practices to foster code modularity, reusability, and maintainability, enabling our AI services to remain flexible for future advancements.",
            "similarity": 0.4919
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 74,
        "score": 0.5392,
        "slug": "flutter-developer",
        "total_count": null
      },
      {
        "display_name": "React Native Developer",
        "kra_matches": [
          {
            "kra_text": "maintain code quality",
            "sentence": "Support and mentor other engineers, contributing to a culture that values technical skill and code quality.",
            "similarity": 0.5498
          },
          {
            "kra_text": "maintain code quality",
            "sentence": "Implement coding best practices to foster code modularity, reusability, and maintainability, enabling our AI services to remain flexible for future advancements.",
            "similarity": 0.5342
          },
          {
            "kra_text": "integrate backend APIs",
            "sentence": "Collaborate with cross-functional teams to integrate AI services into the wider product ecosystem, ensuring a smooth developer experience.",
            "similarity": 0.475
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 73,
        "score": 0.5197,
        "slug": "react-native-developer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 2,
        "score": 0.5,
        "slug": "data-engineer",
        "total_count": 2
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 3,
        "score": 0.5,
        "slug": "ml-engineer",
        "total_count": 2
      },
      {
        "display_name": "Cyber Security Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 5,
        "score": 0.5,
        "slug": "cybersecurity-engineer",
        "total_count": 2
      },
      {
        "display_name": "AR/VR Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 8,
        "score": 0.5,
        "slug": "ar-vr-engineer",
        "total_count": 2
      },
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 1,
        "score": 0.5,
        "slug": "backend-engineer",
        "total_count": 2
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "LLM / GenAI Engineer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 151,
      "score": 0.94,
      "slug": "llm-genai-engineer",
      "total_count": null
    },
    "confidence": 0.94,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "GenAI service development",
      "Software component modularity and reusability",
      "Product ecosystem integration",
      "AI service performance optimization",
      "Cloud-based AI development",
      "Containerized deployment"
    ],
    "matched_kras": [
      "Contribute to the development of GenAI services",
      "Implement coding best practices",
      "Integrate AI services into the wider product ecosystem",
      "Assess and optimize existing AI services",
      "Support and mentor other engineers",
      "Stay informed on the latest AI technologies"
    ],
    "matched_skills": [
      "GenAI",
      "Python",
      "AWS",
      "Azure",
      "GCP",
      "Docker",
      "Kubernetes",
      "cloud-based development",
      "software engineering principles",
      "architectural standards"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=AI / ML; The JD centers on building and optimizing GenAI services in Python, integrating them into products, and working with cloud and deployment technologies, which best matches an LLM/GenAI engineering role.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 16,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": {
      "best_kra_similarity": 0.0,
      "queue_id": 1934,
      "r_and_r_preview": "\u2022 Contribute to the development of GenAI services that are integral to our product offerings and user experiences.\n\u2022 Implement coding best practices to foster code modularity, reusability, and maintai",
      "role_display_name": "LLM / GenAI Engineer",
      "role_slug": "llm-genai-engineer",
      "status": "pending"
    },
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 24885,
        "role_display_name": "LLM / GenAI Engineer",
        "role_slug": "llm-genai-engineer",
        "skill_name": "GenAI",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 24886,
        "role_display_name": "LLM / GenAI Engineer",
        "role_slug": "llm-genai-engineer",
        "skill_name": "Containerization",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 24887,
        "role_display_name": "LLM / GenAI Engineer",
        "role_slug": "llm-genai-engineer",
        "skill_name": "Orchestration",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 24888,
        "role_display_name": "LLM / GenAI Engineer",
        "role_slug": "llm-genai-engineer",
        "skill_name": "Open Source",
        "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": 406,
      "existing_alias_text": "AWS",
      "input_term": "AWS",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "AWS",
        "id": 187,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "aws",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 407,
      "existing_alias_text": "Azure",
      "input_term": "Azure",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Azure",
        "id": 188,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "azure",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 405,
      "existing_alias_text": "GCP",
      "input_term": "GCP",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "GCP",
        "id": 186,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
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        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
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    {
      "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": {
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        "skill_nature": "TOOL",
        "slug": "docker",
        "sub_category_id": 63,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "alias"
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    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1267,
      "existing_alias_text": "Kubernetes",
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        "skill_nature": "PLATFORM",
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        "sub_category_id": 557,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
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      "existing_alias_id": 2367,
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      "input_term": "Open Source",
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    },
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      "slug": "php-backend-developer",
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    },
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      "input_skill": "Python",
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      ]
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        "source": "db"
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      "input_skill": "Python",
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    {
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        "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.",
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        "source": "db"
      },
      "input_skill": "Python",
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      "roles_from_db": [
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        },
        {
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          "slug": "data-engineer",
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          "slug": "devops-engineer",
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          "role_archetype": "Engineering",
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        {
          "display_name": "Node.js Backend Developer",
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        "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
        "slug": "cloud-security-posture-tools",
        "source": "db"
      },
      "input_skill": "AWS",
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      "roles_from_db": [
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        },
        {
          "display_name": "Cyber Security Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
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        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Vendor Product Families",
        "id": 477,
        "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
        "slug": "vendor-product-families",
        "source": "db"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
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          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
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        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms",
        "id": 20,
        "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
        "slug": "cloud-platforms",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
          "id": 83,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "dotnet-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        },
        {
          "display_name": "Cyber Security Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        },
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        },
        {
          "display_name": "Go Backend Developer",
          "id": 81,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Java Backend Developer",
          "id": 79,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "java-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Kotlin Backend Developer",
          "id": 84,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        },
        {
          "display_name": "Node.js Backend Developer",
          "id": 82,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
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              "slug": "ml-ops-engineer",
              "source": "db"
            },
            {
              "display_name": "Node.js Backend Developer",
              "id": 82,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "node-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Scala Backend Developer",
              "id": 87,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "scala-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Platforms for AI Deployment",
            "id": 211,
            "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
            "slug": "cloud-platforms-for-ai-deployment",
            "source": "db"
          },
          "input_skill": "GCP",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AI Engineer",
              "id": 13,
              "rationale": null,
              "role_archetype": null,
              "slug": "ai-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Provider Platforms",
            "id": 131,
            "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
            "slug": "cloud-provider-platforms",
            "source": "db"
          },
          "input_skill": "GCP",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            },
            {
              "display_name": "Cloud Security Engineer",
              "id": 23,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-security-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Security Posture Tools",
            "id": 64,
            "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
            "slug": "cloud-security-posture-tools",
            "source": "db"
          },
          "input_skill": "GCP",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Security Engineer",
              "id": 23,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-security-engineer",
              "source": "db"
            },
            {
              "display_name": "Cyber Security Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "GCP",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Docker",
          "alias_type": "CANONICAL",
          "id": 198,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 13,
        "display_name": "Docker",
        "id": 61,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "docker",
        "sub_category_id": 63,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Containerization and Image Builds",
            "id": 152,
            "rationale": "Container image creation, tagging, hardening, and registry workflows used to package services for deployment. This is coherent because DevOps often owns the build-to-image path that feeds runtime environments.",
            "slug": "containerization-and-image-builds",
            "source": "db"
          },
          "input_skill": "Docker",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Deployment and Cloud Platforms",
            "id": 418,
            "rationale": "Platform-as-a-Service and container environments for deploying Ruby applications.",
            "slug": "deployment-and-cloud-platforms",
            "source": "db"
          },
          "input_skill": "Docker",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Ruby Backend Developer",
              "id": 85,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "ruby-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Deployment and Runtime Configuration",
            "id": 13,
            "rationale": "Configuration and release artifacts that control how backend services run in environments. Includes environment variables, manifests, feature flags, and release-safe configuration management.",
            "slug": "deployment-and-runtime-configuration",
            "source": "db"
          },
          "input_skill": "Docker",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": ".NET Backend Developer",
              "id": 83,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "dotnet-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Backend Developer",
              "id": 1,
              "rationale": null,
              "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
              "slug": "backend-engineer",
              "source": "db"
            },
            {
              "display_name": "Go Backend Developer",
              "id": 81,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "go-backend-developer",
              "source": "db"
            },
            {
              "display_name": "PHP Backend Developer",
              "id": 86,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "php-backend-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Docker",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Kubernetes",
          "alias_type": "CANONICAL",
          "id": 1267,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Kubernetes 1.0+",
          "alias_type": "VERSION",
          "id": 1271,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Kubernetes 1.x",
          "alias_type": "VERSION",
          "id": 1270,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Kubernetes v1",
          "alias_type": "VERSION",
          "id": 1269,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "k8s",
          "alias_type": "VERSION",
          "id": 1268,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "kubernetes 1.x",
          "alias_type": "VERSION",
          "id": 1400,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "kubernetes latest",
          "alias_type": "VERSION",
          "id": 1401,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "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"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Container Orchestration Platforms",
            "id": 134,
            "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"
          },
          "input_skill": "Kubernetes",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Kubernetes for ML Workloads",
            "id": 47,
            "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.",
            "slug": "kubernetes-for-ml-workloads",
            "source": "db"
          },
          "input_skill": "Kubernetes",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Kubernetes",
      "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": "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
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Orchestration",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Container Orchestration",
          "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": "orchestration",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "open-source",
          "alias_type": "CANONICAL",
          "id": 2367,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 2,
        "display_name": "open-source",
        "id": 1472,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "open-source",
        "sub_category_id": 1111,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "Open Source",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Open Source",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "GenAI",
    "Containerization",
    "Orchestration"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "LLM / GenAI Engineer",
    "id": 151,
    "rationale": "Domain=AI / ML; The JD centers on building and optimizing GenAI services in Python, integrating them into products, and working with cloud and deployment technologies, which best matches an LLM/GenAI engineering role.",
    "role_archetype": null,
    "slug": "llm-genai-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "GenAI",
      "tag": "new"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "AWS",
      "tag": "in_db"
    },
    {
      "skill": "Azure",
      "tag": "in_db"
    },
    {
      "skill": "GCP",
      "tag": "in_db"
    },
    {
      "skill": "Docker",
      "tag": "in_db"
    },
    {
      "skill": "Kubernetes",
      "tag": "in_db"
    },
    {
      "skill": "Containerization",
      "tag": "new"
    },
    {
      "skill": "Orchestration",
      "tag": "new"
    },
    {
      "skill": "Open Source",
      "tag": "in_db"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 151,
        "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": 151,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 151,
        "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": 151,
        "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": 151,
        "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": 151,
        "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": 151,
        "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",
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