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Pipeline run

5c009ee0-a15e-4fc5-8eb7-e06d52fbf350

Pipeline LLM cost (USD)
API 1: $0.0043 API 2: $0.0007 API 3: $0.0000 Total: $0.0050

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · Full-stack AI application development
Build full-stack AI apps with Claude, from Python/FastAPI backends and PostgreSQL data layers to React UIs, plus RAG/prompt orchestration and enterprise integrations.
"Design and develop AI-driven applications leveraging Claude (Anthropic) models"
Tech stack maturity
Mainstream Modern
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): Claude
Frameworks (×2): Pinecone
Models / concepts (×3): Anthropic, RAG, LLM, LLMs, prompt engineering, multi-agent, function calling, AI
Evidence — skills matched in JD (25)
Anthropic Claude Python FastAPI Flask React.js JavaScript TypeScript PostgreSQL REST Microservices RAG Prompt Engineering Agent Frameworks Function Calling Git CI/CD Django AWS Azure GCP Azure AI Search Pinecone FAISS Docker Kubernetes
Skill cluster (12 dimension groups, role-scoped)
Cloud Platforms for AI Deployment
AWS Azure GCP
Web Application Frameworks
FastAPI Flask Django
JavaScript and TypeScript
JavaScript TypeScript
API Interface and Contract Design
REST
Containerization and Image Builds
Docker
Kubernetes for ML Workloads
Kubernetes
LLM Operations and Orchestration
Pinecone
ML Frameworks and Libraries
FAISS
Python Programming
Python
Relational Database Usage
PostgreSQL
Structured Output Integration
Function Calling
Cross-cutting / unaligned
Anthropic Claude React.js Microservices RAG Prompt Engineering Agent Frameworks Git CI/CD Azure AI Search
Show KRA description ↓
We are seeking a skilled AI Application Developer to support ongoing AI initiatives. The ideal candidate will have hands-on experience building AI-powered applications using modern LLMs (specifically Anthropic Claude) and full-stack development expertise across web technologies. Design and develop AI-driven applications leveraging Claude (Anthropic) models Build and integrate backend services using Python-based frameworks (e.g., FastAPI, Flask) Develop responsive and scalable front-end applications using React.js Design and manage relational databases (preferably PostgreSQL) Implement end-to-end full-stack solutions, including APIs, UI, and data layers Integrate LLM capabilities into enterprise applications (RAG, prompt orchestration, workflows) Collaborate with cross-functional teams including product owners, infrastructure and DevOps Ensure code quality, security, scalability, and performance best practices 3–7 years of experience in full-stack development Strong experience with Claude (Anthropic) or similar LLM-based application development Proficiency in Python and modern backend frameworks (FastAPI/Flask/Django) Solid experience with React.js and modern JavaScript/TypeScript Hands-on experience with PostgreSQL or comparable relational databases Experience with REST APIs, microservices architecture, and integration patterns Experience with prompt engineering, RAG, and AI application design patterns, multi-agent orchestration, Experience with Agent Frameworks, Claude Tool/plugin (function calling) integration, hooks/lifecycle management, reusable skills design Experience with version control systems (Git) and CI/CD pipelines Experience with cloud platforms (AWS, Azure, or GCP) Experience with vector databases (e.g., Azure AI Search, Pinecone, FAISS etc.) Understanding of enterprise system integrations Exposure to containerization (Docker, Kubernetes) Knowledge of security and compliance requirements for AI applications

Signals

Skill backend-engineer
0.38
Alias full-stack-engineer
1.00
KRA full-stack-engineer
0.67
Status: completed Created: 2026-05-23T23:02:56.652575Z Updated: 2026-05-23T23:03:02.846558Z API 3 duration: 482 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

AI Engineer

slug: ai-engineer · id: 13 · source: db

The role requires expertise in Python, FastAPI, React.js, and microservices, aligning closely with the AI Application Developer title.

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
0
Skipped

Job description

Role Overview:



We are seeking a skilled AI Application Developer to support ongoing AI initiatives. The ideal candidate will have hands-on experience building AI-powered applications using modern LLMs (specifically Anthropic Claude) and full-stack development expertise across web technologies.



Key Responsibilities:



Design and develop AI-driven applications leveraging Claude (Anthropic) models
Build and integrate backend services using Python-based frameworks (e.g., FastAPI, Flask)
Develop responsive and scalable front-end applications using React.js
Design and manage relational databases (preferably PostgreSQL)
Implement end-to-end full-stack solutions, including APIs, UI, and data layers
Integrate LLM capabilities into enterprise applications (RAG, prompt orchestration, workflows)
Collaborate with cross-functional teams including product owners, infrastructure and DevOps
Ensure code quality, security, scalability, and performance best practices


Required Skills:



3–7 years of experience in full-stack development
Strong experience with Claude (Anthropic) or similar LLM-based application development
Proficiency in Python and modern backend frameworks (FastAPI/Flask/Django)
Solid experience with React.js and modern JavaScript/TypeScript
Hands-on experience with PostgreSQL or comparable relational databases
Experience with REST APIs, microservices architecture, and integration patterns
Experience with prompt engineering, RAG, and AI application design patterns, multi-agent orchestration,
Experience with Agent Frameworks, Claude Tool/plugin (function calling) integration, hooks/lifecycle management, reusable skills design
Experience with version control systems (Git) and CI/CD pipelines


Preferred Qualifications:



Experience with cloud platforms (AWS, Azure, or GCP)
Experience with vector databases (e.g., Azure AI Search, Pinecone, FAISS etc.)
Understanding of enterprise system integrations
Exposure to containerization (Docker, Kubernetes)
Knowledge of security and compliance requirements for AI applications

Skills from this JD

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

Anthropic Claude 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
AI Tools
Sub-category
general
Skill nature
TOOL
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

  • 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

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 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)
FastAPI Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: FastAPI id=1201 · fastapi

Aliases — catalog

  • FastAPI (CANONICAL) primary

Context tags (catalog)

API documentation ASGI CORS JSON JSON Schema OAuth2 OpenAPI Pydantic RESTful Starlette UVicorn WebSocket async async programming data validation dependency injection middleware path parameters query parameters type hints uvicorn

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Web Framework
Vendor
Sebastián Ramírez
License
mit
Year introduced
2018
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: FastAPI appears in many Python backend job postings and has strong GitHub adoption; it’s now a common choice for API development alongside Flask/Django rather than a niche tool.

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)

  • 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)
Flask Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Flask id=1344 · flask

Aliases — catalog

  • Flask (CANONICAL) primary
  • flask 2 (VERSION)
  • flask 2.x (VERSION)
  • flask 3 (VERSION)
  • flask 3.x (VERSION)
  • flask2 (VERSION)
  • flask3 (VERSION)
  • flask>=3 (VERSION)

Context tags (catalog)

API Blueprints Flask-Migrate Flask-RESTful Flask-SQLAlchemy Flask-WTF JSON Jinja2 RESTful RESTful APIs SQLAlchemy Werkzeug debugging deployment gunicorn middleware routing session management template rendering unit testing virtual environments virtualenv

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Web Framework
Vendor
Pallets Projects
License
bsd
Year introduced
2010
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
3.x

Maturity reasoning: Flask appears in many Python web developer job postings and remains a common lightweight framework in hiring pipelines, though often alongside Django/FastAPI rather than as a niche tool.

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)

  • 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)
Django Secondary 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)

  • Web Application Frameworks Catalog dimension db id 2

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React.js Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: React.js id=514 · react-js

Aliases — catalog

  • React 0.1 (VERSION)
  • React 0.10 (VERSION)
  • React 0.11 (VERSION)
  • React 0.12 (VERSION)
  • React 0.13 (VERSION)
  • React 0.14 (VERSION)
  • React 0.2 (VERSION)
  • React 0.3 (VERSION)
  • React 0.4 (VERSION)
  • React 0.5 (VERSION)
  • React 0.6 (VERSION)
  • React 0.7 (VERSION)
  • React 0.8 (VERSION)
  • React 0.9 (VERSION)
  • React 15 (VERSION)
  • React 16 (VERSION)
  • React 17 (VERSION)
  • React 18 (VERSION)
  • React.js (CANONICAL)
  • React.js 15 (VERSION)
  • React.js 16 (VERSION)
  • React.js 17 (VERSION)
  • React.js 18 (VERSION)

Context tags (catalog)

JSX Material UI Next.js React Router Redux SSR Tailwind CSS TypeScript component lifecycle hooks props state management useEffect useState virtual DOM

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Frontend Ui Framework
Vendor
Meta
License
mit
Year introduced
2013
Confidence
0.98
Version strategy
SEPARATE_ENTITY
Version tag
18

Maturity reasoning: React.js is a hiring-pipeline staple with very high JD volume across frontend roles and broad ecosystem adoption; it remains one of the most commonly requested UI frameworks on job boards and in GitHub usage trends.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
363
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)
JavaScript Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: JavaScript id=607 · javascript

Aliases — catalog

  • JavaScript (CANONICAL) primary
  • ES2015 (VERSION)
  • ES2016 (VERSION)
  • ES2017 (VERSION)
  • ES2018 (VERSION)
  • ES2019 (VERSION)
  • ES2020 (VERSION)
  • ES2021 (VERSION)
  • ES2022 (VERSION)
  • ES2023 (VERSION)
  • ES2024 (VERSION)
  • ES5 (VERSION)
  • ES6 (VERSION)
  • JavaScript ES2015 (VERSION)
  • JavaScript ES2020 (VERSION)
  • JavaScript ES6 (VERSION)
  • modern JavaScript (VERSION)

Context tags (catalog)

AJAX Angular Babel DOM DOM manipulation ES6 Express JSON Node.js REST RESTful React TypeScript Vue Vue.js Webpack async/await asynchronous callback callback functions closure event-driven jQuery npm promises

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
Mozilla
License
mpl
Year introduced
1995
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: JavaScript appears in a very high volume of job postings across frontend, backend, and full-stack roles, and remains a core language in major ecosystems like Node.js and React.

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)

  • Cross-Platform App Languages Catalog dimension db id 167

    Library dimension (catalog)

    Roles linked in library: Hybrid Mobile Developer

  • JavaScript and TypeScript Catalog dimension db id 114

    Library dimension (catalog)

    Roles linked in library: Frontend Developer

  • Pega Programming Languages & DSLs Catalog dimension db id 267

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cross-Platform App Languages
cross-platform-app-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript and TypeScript
javascript-and-typescript
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Pega Programming Languages & DSLs
pega-programming-languages-dsls
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)
TypeScript Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: TypeScript id=524 · typescript

Aliases — catalog

  • TypeScript (CANONICAL) primary
  • TypeScript 5 (VERSION)
  • TypeScript 5.x (VERSION)
  • ts (VERSION)
  • ts5 (VERSION)
  • typescript 5 (VERSION)
  • typescript 5.x (VERSION)
  • typescript5 (VERSION)

Context tags (catalog)

Angular Async/Await Decorator Deno ESLint Generics GraphQL Interfaces JavaScript Jest NestJS Next.js Node.js Promise React Redux RxJS TypeORM Vite Vue Vue.js Webpack async/await decorators generics interfaces module resolution npm strict mode tsconfig type annotations type guards type inference type safety yarn

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
Microsoft
License
apache_2
Year introduced
2012
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: TypeScript is a hiring-pipeline staple: it appears in a large share of modern web/frontend and Node.js job descriptions, and major frameworks like Angular and Next.js recommend it by default.

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)

  • Cross-Platform App Languages Catalog dimension db id 167

    Library dimension (catalog)

    Roles linked in library: Hybrid Mobile Developer

  • JavaScript and TypeScript Catalog dimension db id 114

    Library dimension (catalog)

    Roles linked in library: Frontend Developer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cross-Platform App Languages
cross-platform-app-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript and TypeScript
javascript-and-typescript
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 for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PostgreSQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: PostgreSQL id=16 · postgresql

Aliases — catalog

  • PostgreSQL (CANONICAL) primary
  • PG 13 (VERSION)
  • PG 14 (VERSION)
  • PG 15 (VERSION)
  • PG 16 (VERSION)
  • PostgreSQL 13 (VERSION)
  • PostgreSQL 14 (VERSION)
  • PostgreSQL 15 (VERSION)
  • PostgreSQL 16 (VERSION)
  • Postgres 13 (VERSION)
  • Postgres 14 (VERSION)
  • Postgres 15 (VERSION)
  • Postgres 16 (VERSION)
  • pg10 (VERSION)
  • pg11 (VERSION)
  • pg12 (VERSION)
  • pg13 (VERSION)
  • pg14 (VERSION)
  • pg15 (VERSION)
  • pg16 (VERSION)
  • postgres (VERSION)
  • postgresql 10 (VERSION)
  • postgresql 11 (VERSION)
  • postgresql 12 (VERSION)
  • postgresql 13 (VERSION)
  • postgresql 14 (VERSION)
  • postgresql 15 (VERSION)
  • postgresql 16 (VERSION)
  • postgresql-16 (VERSION)
  • postgresql10 (VERSION)
  • postgresql11 (VERSION)
  • postgresql12 (VERSION)
  • postgresql13 (VERSION)
  • postgresql14 (VERSION)
  • postgresql15 (VERSION)
  • postgresql16 (VERSION)

Context tags (catalog)

ACID EXPLAIN JSONB PL/pgSQL PostGIS SQL VACUUM backup data integrity database migration extensions indexes indexing joins migration partitioning performance tuning pgAdmin query optimization replication schema stored procedures table partitioning transaction transactions triggers views

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Relational Database
Vendor
PostgreSQL Global Development Group
License
other_open
Year introduced
1996
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: PostgreSQL appears in a large share of backend/data engineering job postings and is a default managed option across AWS RDS, GCP Cloud SQL, and Azure Database, indicating broad hiring-pipeline adoption.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
29
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Relational Data Modeling Catalog dimension db id 216

    Library dimension (catalog)

    Roles linked in library: Fullstack Developer

  • Relational Database Design Catalog dimension db id 4

    Library dimension (catalog)

    Roles linked in library: Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Relational Data Modeling
relational-data-modeling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: REST id=11 · rest

Aliases — catalog

  • REST (CANONICAL) primary

Context tags (catalog)

API API design API versioning CRUD DELETE GET HATEOAS HTTP JSON OAuth OAuth2 OpenAPI POST PUT Postman RESTful Swagger URI Webhooks XML authentication client-server content negotiation endpoint endpoints middleware resource resource-oriented serialization stateless status codes versioning web services

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Api Architecture Style
Year introduced
2000
Confidence
0.88
Version strategy
NOT_APPLICABLE

Maturity reasoning: REST is a default API architecture in many job descriptions and is widely supported by major vendors/frameworks; OpenAPI and RESTful endpoints remain standard in hiring pipelines.

Skill profile (library / DB)

Skill nature
PROTOCOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
10
Sub-category id
1485
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • API Design and Contracts Catalog dimension db id 3

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer

  • Integration Protocols & Standards Catalog dimension db id 271

    Library dimension (catalog)

    Roles linked in library: Pega Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
API Design and Contracts
api-design-and-contracts
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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

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 skipped (dimension not under chosen role)
RAG Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: RAG id=1194 · rag

Aliases — catalog

  • RAG (CANONICAL)

Context tags (catalog)

AI applications contextualization data augmentation fine-tuning generation information retrieval knowledge integration machine learning model training natural language processing prompt engineering retrieval semantic search transformer models user intent

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Retrieval Augmented Generation
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: RAG appears in many recent AI/ML job descriptions and vendor docs, but it is still not a universal baseline skill like Python or SQL; market demand is rising fast rather than fully standardized.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
904
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)
Prompt Engineering Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Prompt engineering id=1207 · prompt-engineering

Aliases — catalog

  • Prompt engineering (CANONICAL)

Context tags (catalog)

AI alignment contextual prompts data annotation evaluation metrics feedback loops fine-tuning iterative testing language models model training natural language processing prompt design prompt optimization prompt templates user experience user intent

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Prompt Engineering
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: Prompt engineering is increasingly listed in AI/LLM job descriptions and vendor docs, but it’s still not a universal hiring staple like Python or AWS.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
914
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)
Agent Frameworks 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
AI Frameworks
Sub-category
general
Skill nature
CONCEPT
Volatility
FAST
Typical lifespan
SHORT_LIVED
Version strategy
VERSIONED
Function Calling Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: function calling id=1278 · function-calling

Aliases — catalog

  • function calling (CANONICAL) primary

Context tags (catalog)

argument passing asynchronous callback closure event-driven first-class function function signature functional programming higher-order function lambda method invocation recursion return value scope variable arguments

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Function Calling Concept
Confidence
0.70
Version strategy
NOT_APPLICABLE

Maturity reasoning: Appears increasingly in LLM vendor docs and job postings for AI app roles, but is still far from universal compared with core backend skills.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
943
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Structured Output Integration Catalog dimension db id 204

    Library dimension (catalog)

    Roles linked in library: AI Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Structured Output Integration
structured-output-integration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Git Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Git id=1002 · git

Aliases — catalog

  • Git (CANONICAL)

Context tags (catalog)

CI/CD GitHub GitLab branching checkout clone commit fork merging pull request rebase remote repository stash versioning

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Version Control Tool
Vendor
Linus Torvalds
License
gpl_v2
Year introduced
2005
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Git is a hiring-pipeline staple: it appears in the vast majority of software engineering job descriptions and is the default VCS on GitHub/GitLab/Bitbucket.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
730
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)
CI/CD Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: CI/CD id=1190 · ci-cd

Aliases — catalog

  • CI/CD (CANONICAL)

Context tags (catalog)

Ansible CircleCI Docker GitLab CI Jenkins Kubernetes Terraform Travis CI automated testing build automation continuous deployment continuous integration deployment pipelines monitoring version control

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Ci Cd Process
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: CI/CD appears in a large share of software engineering JDs and is a standard requirement across DevOps, platform, and backend roles; major vendors like GitHub, GitLab, and AWS all center product roadmaps on CI/CD pipelines.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
900
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

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

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD for Machine Learning
ci-cd-for-machine-learning
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: Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, ML Engineer, MLOps Engineer

  • 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)
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: Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, ML Engineer, MLOps Engineer

  • Cloud Platforms & Managed Services Catalog dimension db id 221

    Library dimension (catalog)

    Roles linked in library: Fullstack 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 & 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)
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: Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, ML Engineer, MLOps Engineer

  • 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)
Azure AI Search Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Pinecone Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Pinecone id=242 · pinecone

Aliases — catalog

  • Pinecone (CANONICAL) primary

Context tags (catalog)

ANN API integration LangChain OpenAI embeddings RAG analytics cloud-native data pipelines data retrieval distributed architecture embedding embeddings high-dimensional data indexing machine learning metadata filtering metadata management namespace nearest neighbor performance tuning query optimization real-time indexing retrieval augmented generation scalability semantic search similarity search upsert vector index vector search

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Vector Database Platform
Vendor
Pinecone
License
unknown
Year introduced
2021
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: Pinecone appears in a growing number of AI/vector-search job postings and vendor docs, but it is still far from universal compared with PostgreSQL or AWS.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
177
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • LLM Operations and Orchestration Catalog dimension db id 49

    Library dimension (catalog)

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

  • Vector Databases Catalog dimension db id 198

    Library dimension (catalog)

    Roles linked in library: AI Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
LLM Operations and Orchestration
llm-operations-and-orchestration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Vector Databases
vector-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
FAISS Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: FAISS id=1184 · faiss

Aliases — catalog

  • FAISS (CANONICAL)

Context tags (catalog)

GPU acceleration approximate nearest neighbors clustering data retrieval embedding high-dimensional indexing machine learning nearest neighbor performance tuning quantization scalability search algorithms similarity search vector search

Stored enrichment (catalog DB)

Category
Library
Sub-category
Vector Search Library
Vendor
Facebook
License
apache_2
Year introduced
2017
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: FAISS appears in growing number of AI/vector-search job descriptions and is widely used in RAG stacks, but it is still less universal than PostgreSQL or Kubernetes and often paired with managed vector DBs.

Skill profile (library / DB)

Skill nature
LIBRARY
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
7
Sub-category id
894
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ML Frameworks and Libraries Catalog dimension db id 40

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ML Frameworks and Libraries
ml-frameworks-and-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Frontend Development
d_init_01
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
654
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 Runtime Configuration Catalog dimension db id 13

    Library dimension (catalog)

    Roles linked in library: 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 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)

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 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)
FastAPI in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Flask in_db
React Frontend Development
d_init_01
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 skipped (dimension not under chosen role)
React.js in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript in_db
Cross-Platform App Languages
cross-platform-app-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript in_db
JavaScript and TypeScript
javascript-and-typescript
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript in_db
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
TypeScript in_db
Cross-Platform App Languages
cross-platform-app-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
TypeScript in_db
JavaScript and TypeScript
javascript-and-typescript
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
TypeScript in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
TypeScript in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PostgreSQL in_db
Relational Data Modeling
relational-data-modeling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PostgreSQL in_db
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST in_db
API Design and Contracts
api-design-and-contracts
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST in_db
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Microservices in_db
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
RAG in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Prompt Engineering in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Function Calling in_db
Structured Output Integration
structured-output-integration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Git in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
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)
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)
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)
Pinecone in_db
LLM Operations and Orchestration
llm-operations-and-orchestration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Pinecone in_db
Vector Databases
vector-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
FAISS in_db
ML Frameworks and Libraries
ml-frameworks-and-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
FAISS in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker in_db
Containerization and Image Builds
containerization-and-image-builds
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Docker in_db
Deployment and Runtime Configuration
deployment-and-runtime-configuration
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Kubernetes in_db
Container Orchestration Platforms
container-orchestration-platforms
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Kubernetes in_db
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
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Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Anthropic Claude | type=AI Tools subtype=general nature=TOOL lifespan=SHORT_LIVED
canonical_skill_proposed Agent Frameworks | type=AI Frameworks subtype=general nature=CONCEPT lifespan=SHORT_LIVED
canonical_skill_proposed Azure AI Search | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleAI Application Developer
Experience3–7 years of experience in full-stack development
DomainSoftware & SaaS Products
JD type pass
Show raw JSON
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API 1 — extract-from-jd click to toggle
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          "display_name": "Frontend Developer",
          "id": 7,
          "rationale": null,
          "role_archetype": null,
          "slug": "frontend-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": "TypeScript",
      "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"
        }
      ]
    },
    {
      "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": "TypeScript",
      "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": "Relational Data Modeling",
        "id": 216,
        "rationale": "Schema design and query-aware persistence for product features. Full stack engineers use this to shape tables, relationships, migrations, and transactional behavior that support application flows.",
        "slug": "relational-data-modeling",
        "source": "db"
      },
      "input_skill": "PostgreSQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Fullstack Developer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Relational Database Design",
        "id": 4,
        "rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
        "slug": "relational-database-design",
        "source": "db"
      },
      "input_skill": "PostgreSQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "API Design and Contracts",
        "id": 3,
        "rationale": "Designing request/response shapes and the rules that govern client-server interaction. This cluster is coherent because full stack engineers often own the contract between UI behavior and backend implementation.",
        "slug": "api-design-and-contracts",
        "source": "db"
      },
      "input_skill": "REST",
      "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"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Integration Protocols \u0026 Standards",
        "id": 271,
        "rationale": "Standards and protocols for integrating Pega applications.",
        "slug": "integration-protocols-standards",
        "source": "db"
      },
      "input_skill": "REST",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Pega Developer",
          "id": 24,
          "rationale": null,
          "role_archetype": null,
          "slug": "pega-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Microservices and Distributed Systems",
        "id": 9,
        "rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
        "slug": "microservices-and-distributed-systems",
        "source": "db"
      },
      "input_skill": "Microservices",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "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": "RAG",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "Prompt Engineering",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Structured Output Integration",
        "id": 204,
        "rationale": "Turning model responses into reliable application data that downstream code can consume. This dimension covers schema-constrained generation, parsing, validation, and mapping outputs into product workflows.",
        "slug": "structured-output-integration",
        "source": "db"
      },
      "input_skill": "Function Calling",
      "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": "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": "Git",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "CI/CD Pipeline Platforms",
        "id": 150,
        "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
        "slug": "ci-cd-pipeline-platforms",
        "source": "db"
      },
      "input_skill": "CI/CD",
      "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": "CI/CD for Machine Learning",
        "id": 56,
        "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
        "slug": "ci-cd-for-machine-learning",
        "source": "db"
      },
      "input_skill": "CI/CD",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms",
        "id": 20,
        "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
        "slug": "cloud-platforms",
        "source": "db"
      },
      "input_skill": "AWS",
      "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": "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": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud 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": "AWS",
      "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": "AWS",
      "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": "AWS",
      "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"
        }
      ]
    },
    {
      "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": "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": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms \u0026 Managed Services",
        "id": 221,
        "rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
        "slug": "cloud-platforms-managed-services",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Fullstack Developer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "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": "Azure",
      "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": "Azure",
      "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": "Azure",
      "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"
        }
      ]
    },
    {
      "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": "GCP",
      "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": "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": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud 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"
        }
      ]
    },
    {
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              "display_name": "Fullstack Developer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "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": "Azure",
          "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": "Azure",
          "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": "Azure",
          "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": "Azure",
      "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": "GCP",
          "alias_type": "CANONICAL",
          "id": 405,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 9,
        "display_name": "GCP",
        "id": 186,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "gcp",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "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": "GCP",
          "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": "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": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud 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": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Azure AI Search",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Cloud Platforms",
          "skill_nature": "PLATFORM",
          "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": "azure-ai-search",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Pinecone",
          "alias_type": "CANONICAL",
          "id": 503,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 9,
        "display_name": "Pinecone",
        "id": 242,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "pinecone",
        "sub_category_id": 177,
        "typical_lifespan": "EVERGREEN",
        "volatility": "EMERGING"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "LLM Operations and Orchestration",
            "id": 49,
            "rationale": "Operational stack for building, serving, evaluating, and orchestrating LLM-based systems. This includes vector retrieval, prompt workflows, LLM serving, and observability for generative applications.",
            "slug": "llm-operations-and-orchestration",
            "source": "db"
          },
          "input_skill": "Pinecone",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AI Engineer",
              "id": 13,
              "rationale": null,
              "role_archetype": null,
              "slug": "ai-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Vector Databases",
            "id": 198,
            "rationale": "Specialized storage and indexing systems used to persist embeddings and support similarity search. This is a distinct vendor-family cluster because AI features often depend on a concrete vector store choice and its operational behavior.",
            "slug": "vector-databases",
            "source": "db"
          },
          "input_skill": "Pinecone",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AI Engineer",
              "id": 13,
              "rationale": null,
              "role_archetype": null,
              "slug": "ai-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Pinecone",
      "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": "FAISS",
          "alias_type": "CANONICAL",
          "id": 1820,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 7,
        "display_name": "FAISS",
        "id": 1184,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LIBRARY",
        "slug": "faiss",
        "sub_category_id": 894,
        "typical_lifespan": "EVERGREEN",
        "volatility": "EMERGING"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "ML Frameworks and Libraries",
            "id": 40,
            "rationale": "Core libraries used to define models, train them, run inference, and evaluate predictive performance. These frameworks shape how ML engineers express model architectures and training loops.",
            "slug": "ml-frameworks-and-libraries",
            "source": "db"
          },
          "input_skill": "FAISS",
          "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": "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": "FAISS",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "FAISS",
      "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": 654,
        "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 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": "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"
            }
          ]
        }
      ],
      "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
    }
  ],
  "unmatched_skills": [
    "Anthropic Claude",
    "Agent Frameworks",
    "Azure AI Search"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "AI Engineer",
    "id": 13,
    "rationale": "The role requires expertise in Python, FastAPI, React.js, and microservices, aligning closely with the AI Application Developer title.",
    "role_archetype": "Engineering role focused on building AI applications.",
    "slug": "ai-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Anthropic Claude",
      "tag": "new"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "FastAPI",
      "tag": "in_db"
    },
    {
      "skill": "Flask",
      "tag": "in_db"
    },
    {
      "skill": "Django",
      "tag": "in_db"
    },
    {
      "skill": "React.js",
      "tag": "in_db"
    },
    {
      "skill": "JavaScript",
      "tag": "in_db"
    },
    {
      "skill": "TypeScript",
      "tag": "in_db"
    },
    {
      "skill": "PostgreSQL",
      "tag": "in_db"
    },
    {
      "skill": "REST",
      "tag": "in_db"
    },
    {
      "skill": "Microservices",
      "tag": "in_db"
    },
    {
      "skill": "RAG",
      "tag": "in_db"
    },
    {
      "skill": "Prompt Engineering",
      "tag": "in_db"
    },
    {
      "skill": "Agent Frameworks",
      "tag": "new"
    },
    {
      "skill": "Function Calling",
      "tag": "in_db"
    },
    {
      "skill": "Git",
      "tag": "in_db"
    },
    {
      "skill": "CI/CD",
      "tag": "in_db"
    },
    {
      "skill": "AWS",
      "tag": "in_db"
    },
    {
      "skill": "Azure",
      "tag": "in_db"
    },
    {
      "skill": "GCP",
      "tag": "in_db"
    },
    {
      "skill": "Azure AI Search",
      "tag": "new"
    },
    {
      "skill": "Pinecone",
      "tag": "in_db"
    },
    {
      "skill": "FAISS",
      "tag": "in_db"
    },
    {
      "skill": "Docker",
      "tag": "in_db"
    },
    {
      "skill": "Kubernetes",
      "tag": "in_db"
    }
  ],
  "llm_cost_api1_usd": null,
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        "roles_from_db": [
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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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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