Pipeline run
553d18ce-336f-40ff-a8dd-fdabe5550429
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
Gen AI, Python, Azure • Strong experience in Python programming language - Must. • Experience in REST APIs, Fast APIs, Graph APIs, SQL Alchemy. • Good experience in Azure Services like DataLake, Azur…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
LLM / GenAI Engineer
domain · AI / ML CASE DOMAINslug: llm-genai-engineer · id: 151 · source: db
Domain=AI / ML; The JD is centered on building GenAI applications with Python, Azure services, RAG, embeddings, prompting, and GenAI frameworks, which best matches an LLM/GenAI engineering role.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Job Title: Data Engineer (Gen AI) Must Have Skills: Gen AI, Python, Azure Exp: 5-8 Yrs • Strong experience in Python programming language - Must. • Experience in REST APIs, Fast APIs, Graph APIs, SQL Alchemy. • Good experience in Azure Services like DataLake, Azure SQL, Function App, Azure Cognitive Search. • Good Understanding on Chunking, Embeddings, vectorization, indexing, Prompting, Hallucinations, RAG • Hands on experience in DevOps, create pull PRs and maintain code repositories. • Strong communication skills and ability to collaborate effectively with team members. • Different GenAI frameworks.. security and governance
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
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)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- PSF
- License
- mit
- Year introduced
- 1991
- Confidence
- 0.99
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 3
Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 96
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Security Scripting & DSL Languages Catalog dimension db id 248
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer
-
Programming Languages Catalog dimension db id 1
Library dimension (catalog)
Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer
-
Programming Languages & DSLs Catalog dimension db id 475
Library dimension (catalog)
Roles linked in library: Engineering Manager
-
Programming Languages and Scripting Catalog dimension db id 59
Library dimension (catalog)
Roles linked in library: Cyber Security Engineer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
-
Programming Languages for ML Systems Catalog dimension db id 39
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
-
Programming Languages for XR Catalog dimension db id 97
Library dimension (catalog)
Roles linked in library: AR/VR Engineer
-
Python Programming Catalog dimension db id 290
Library dimension (catalog)
Roles linked in library: Python Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Azure (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Cloud Platform
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2010
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Azure is broadly adopted and frequently appears in cloud/platform job descriptions alongside AWS and GCP; Microsoft’s ongoing enterprise investment and Azure certification demand signal strong hiring-pipeline relevance.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 46
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
-
Cloud Platforms & Managed Services Catalog dimension db id 221
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer
-
Cloud Platforms for AI Deployment Catalog dimension db id 211
Library dimension (catalog)
Roles linked in library: AI Engineer
-
Cloud Provider Platforms Catalog dimension db id 131
Library dimension (catalog)
Roles linked in library: Cloud Architect, Cloud Security Engineer
-
Cloud Security Posture Tools Catalog dimension db id 64
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
-
Vendor Product Families Catalog dimension db id 477
Library dimension (catalog)
Roles linked in library: Engineering Manager
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Vendor Product Families
vendor-product-families
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- REST (CANONICAL) primary
Context tags (catalog)
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
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 2122
- 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, Fullstack Developer
-
API Interface and Contract Design Catalog dimension db id 289
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
-
Integration Protocols & Standards Catalog dimension db id 271
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Standards, Protocols & Compliance Catalog dimension db id 452
Library dimension (catalog)
Roles linked in library: Engineering Manager, Sitecore Dev
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) |
|
API Interface and Contract Design
api-interface-and-contract-design
|
✓ | — | 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) |
|
Standards, Protocols & Compliance
standards-protocols-compliance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- FastAPI (CANONICAL) primary
Context tags (catalog)
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)
-
Web Application Frameworks Catalog dimension db id 2
Library dimension (catalog)
Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer, Java Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Web Application Frameworks
web-application-frameworks
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Web Frameworks
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- SQLAlchemy (CANONICAL) primary
- SQLAlchemy 1 (VERSION)
- SQLAlchemy 1.x (VERSION)
- SQLAlchemy 2 (VERSION)
- SQLAlchemy 2.x (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Library
- Sub-category
- Orm Library
- Vendor
- SQLAlchemy Team
- License
- mit
- Year introduced
- 2005
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: SQLAlchemy appears frequently in Python backend job descriptions and is a standard ORM in the ecosystem; it remains actively maintained with broad GitHub usage and no vendor sunset signal.
Skill profile (library / DB)
- Skill nature
- LIBRARY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 7
- Sub-category id
- 39
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ORMs and Data Access Layers Catalog dimension db id 5
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Fullstack Developer, Fullstack Developer, Java Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Ruby Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ORMs and Data Access Layers
orms-and-data-access-layers
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- Data Storage
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Databases
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Azure Functions (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Serverless Compute Service
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2016
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Broadly listed in cloud/serverless job descriptions and Microsoft actively supports it as a core Azure service; it’s a common hiring-pipeline skill for event-driven apps and APIs.
Skill profile (library / DB)
- Skill nature
- CLOUD_SERVICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 1097
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms & Hosting Providers Catalog dimension db id 278
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Kotlin Backend Developer, Scala Backend Developer, Web Developer
-
Cloud Platforms & Managed Services Catalog dimension db id 221
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
|
✓ | — | 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) |
Aliases — catalog
- Azure Cognitive Search (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Search Service
- Vendor
- Microsoft
- License
- other_open
- Year introduced
- 2017
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Frequently appears in Azure/cloud job descriptions and Microsoft positions it as a core managed search service, with broad enterprise adoption for app search and RAG retrieval.
Skill profile (library / DB)
- Skill nature
- CLOUD_SERVICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 3308
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Search and Content Discovery Catalog dimension db id 356
Library dimension (catalog)
Roles linked in library: Drupal Dev, Sitecore Dev
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Search and Content Discovery
search-and-content-discovery
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- DevOps (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Devops Methodology
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: DevOps appears in a large share of software and platform engineering job descriptions, often alongside CI/CD, Kubernetes, and cloud tooling; it is a standard hiring-pipeline keyword rather than a niche specialty.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 922
- 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
-
Deployment and Release Patterns Catalog dimension db id 140
Library dimension (catalog)
Roles linked in library: Cloud Architect
-
Infrastructure as Code Catalog dimension db id 132
Library dimension (catalog)
Roles linked in library: Cloud Architect, DevOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- DevOps Tools
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- DevOps Tools
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Machine Learning Frameworks
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- FAST
- Typical lifespan
- SHORT_LIVED
- Version strategy
- VERSIONED
Aliases — catalog
- chunking strategies (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Document Processing Methodology
- Confidence
- 0.84
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Appears increasingly in RAG/document-processing JDs and vendor docs, but job-posting volume is still far below staple skills like OCR or vector search.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- EMERGING
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 977
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
RAG Architectures Catalog dimension db id 197
Library dimension (catalog)
Roles linked in library: AI Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
RAG Architectures
rag-architectures
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Aliases — catalog
- Embeddings (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Vector Representation
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Embeddings are a standard ML concept and appear widely in JDs for search, recommendation, and LLM/RAG roles; major vendors like OpenAI, Cohere, and AWS expose embedding APIs, signaling broad adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 905
- 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)
-
Systems Programming Catalog dimension db id 166
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) |
|
Systems Programming
d_init_02
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Machine Learning Frameworks
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- FAST
- Typical lifespan
- SHORT_LIVED
- Version strategy
- VERSIONED
Aliases — catalog
- indexing (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Database Indexing
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Database indexing is a standard requirement in SQL/NoSQL job descriptions and core DB docs; it’s broadly expected for performance tuning rather than a niche specialty.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 2477
- 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, Fullstack Developer, PHP Backend Developer
-
Relational Database Design Catalog dimension db id 4
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
-
Search and Content Discovery Catalog dimension db id 356
Library dimension (catalog)
Roles linked in library: Drupal Dev, Sitecore Dev
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) |
|
Search and Content Discovery
search-and-content-discovery
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Prompt engineering (CANONICAL)
Context tags (catalog)
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Machine Learning Frameworks
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- FAST
- Typical lifespan
- SHORT_LIVED
- Version strategy
- VERSIONED
Aliases — catalog
- retrieval-augmented generation (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Architecture
- Sub-category
- Rag Architecture
- Confidence
- 0.95
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: RAG is increasingly listed in AI/ML job descriptions and vendor docs, with strong GitHub activity around LangChain/LlamaIndex, but it is not yet a universal hiring staple.
Skill profile (library / DB)
- Skill nature
- PATTERN
- Volatility
- EMERGING
- Typical lifespan
- EVERGREEN
- Category id
- 1
- Sub-category id
- 930
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
RAG Architectures Catalog dimension db id 197
Library dimension (catalog)
Roles linked in library: AI Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
RAG Architectures
rag-architectures
|
✓ | — | 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 & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Vendor Product Families
vendor-product-families
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| 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 |
API Interface and Contract Design
api-interface-and-contract-design
|
✓ | — | 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) | |
| REST | in_db |
Standards, Protocols & Compliance
standards-protocols-compliance
|
✓ | — | 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) | |
| FastAPI | in_db |
Web Application Frameworks
web-application-frameworks
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQLAlchemy | in_db |
ORMs and Data Access Layers
orms-and-data-access-layers
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure Functions | in_db |
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure Functions | in_db |
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure Cognitive Search | in_db |
Search and Content Discovery
search-and-content-discovery
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Chunking | new |
RAG Architectures
rag-architectures
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Embeddings | in_db |
ML Frameworks and Libraries
ml-frameworks-and-libraries
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Embeddings | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Embeddings | in_db |
Systems Programming
d_init_02
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Indexing | in_db |
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Indexing | in_db |
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Indexing | in_db |
Search and Content Discovery
search-and-content-discovery
|
✓ | — | 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) | |
| Retrieval-Augmented Generation | in_db |
RAG Architectures
rag-architectures
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Graph API | type=Web Frameworks subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Azure Data Lake | type=Cloud Platforms subtype=Data Storage nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Azure SQL | type=Databases subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Pull Requests | type=DevOps Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Code Repositories | type=DevOps Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Generative AI | type=Machine Learning Frameworks subtype=general nature=CONCEPT lifespan=SHORT_LIVED | |
| canonical_skill_proposed | Vectorization | type=Machine Learning Frameworks subtype=general nature=CONCEPT lifespan=SHORT_LIVED | |
| canonical_skill_proposed | Hallucinations | type=Machine Learning Frameworks subtype=general nature=CONCEPT lifespan=SHORT_LIVED | |
| dimension_skill_link_proposed | Chunking ↔ RAG Architectures |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [],
"experience": {
"max": 8,
"min": 5,
"raw": "5-8 Yrs"
},
"job_locations": [],
"role": "Data Engineer (Gen AI)",
"role_aliases": [
"Data Engineer",
"Gen AI Engineer",
"AI Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Must Have Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Gen AI, Python, Azure",
"last_5_words": "Gen AI, Python, Azure"
},
"text": "Gen AI, Python, Azure",
"word_count": 4
},
{
"bullet_count": 7,
"heading": "Responsibilities",
"heading_was_present": false,
"source_marker": {
"first_5_words": "\u2022 Strong experience in Python",
"last_5_words": "security and governance"
},
"text": "\u2022 Strong experience in Python programming language - Must.\n\u2022 Experience in REST APIs, Fast APIs, Graph APIs, SQL Alchemy.\n\u2022 Good experience in Azure Services like DataLake, Azure SQL, Function App, Azure Cognitive Search.\n\u2022 Good Understanding on Chunking, Embeddings, vectorization, indexing, Prompting, Hallucinations, RAG\n\u2022 Hands on experience in DevOps, create pull PRs and maintain code repositories.\n\u2022 Strong communication skills and ability to collaborate effectively with team members.\n\u2022 Different GenAI frameworks.. security and governance",
"word_count": 83
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Python"
},
{
"is_primary": true,
"skill_name": "Azure"
},
{
"is_primary": true,
"skill_name": "REST"
},
{
"is_primary": true,
"skill_name": "FastAPI"
},
{
"is_primary": false,
"skill_name": "Graph API"
},
{
"is_primary": true,
"skill_name": "SQLAlchemy"
},
{
"is_primary": false,
"skill_name": "Azure Data Lake"
},
{
"is_primary": false,
"skill_name": "Azure SQL"
},
{
"is_primary": false,
"skill_name": "Azure Functions"
},
{
"is_primary": false,
"skill_name": "Azure Cognitive Search"
},
{
"is_primary": false,
"skill_name": "DevOps"
},
{
"is_primary": false,
"skill_name": "Pull Requests"
},
{
"is_primary": false,
"skill_name": "Code Repositories"
},
{
"is_primary": true,
"skill_name": "Generative AI"
},
{
"is_primary": false,
"skill_name": "Chunking"
},
{
"is_primary": false,
"skill_name": "Embeddings"
},
{
"is_primary": false,
"skill_name": "Vectorization"
},
{
"is_primary": false,
"skill_name": "Indexing"
},
{
"is_primary": false,
"skill_name": "Prompt Engineering"
},
{
"is_primary": false,
"skill_name": "Hallucinations"
},
{
"is_primary": false,
"skill_name": "Retrieval-Augmented Generation"
}
],
"jd_role": {
"display_name": "Data Engineer (Gen AI)",
"rationale": null,
"role_aliases": [
"Data Engineer",
"Gen AI Engineer",
"AI Engineer"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [],
"experience": {
"max": 8,
"min": 5,
"raw": "5-8 Yrs"
},
"job_locations": [],
"role": "Data Engineer (Gen AI)",
"role_aliases": [
"Data Engineer",
"Gen AI Engineer",
"AI Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Must Have Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Gen AI, Python, Azure",
"last_5_words": "Gen AI, Python, Azure"
},
"text": "Gen AI, Python, Azure",
"word_count": 4
},
{
"bullet_count": 7,
"heading": "Responsibilities",
"heading_was_present": false,
"source_marker": {
"first_5_words": "\u2022 Strong experience in Python",
"last_5_words": "security and governance"
},
"text": "\u2022 Strong experience in Python programming language - Must.\n\u2022 Experience in REST APIs, Fast APIs, Graph APIs, SQL Alchemy.\n\u2022 Good experience in Azure Services like DataLake, Azure SQL, Function App, Azure Cognitive Search.\n\u2022 Good Understanding on Chunking, Embeddings, vectorization, indexing, Prompting, Hallucinations, RAG\n\u2022 Hands on experience in DevOps, create pull PRs and maintain code repositories.\n\u2022 Strong communication skills and ability to collaborate effectively with team members.\n\u2022 Different GenAI frameworks.. security and governance",
"word_count": 83
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "553d18ce-336f-40ff-a8dd-fdabe5550429",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "AI Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 13,
"score": 1.0,
"slug": "ai-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "DevOps Engineer",
"kra_matches": [
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "Hands on experience in DevOps, create pull PRs and maintain code repositories.",
"similarity": 0.5441
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "Strong communication skills and ability to collaborate effectively with team members.",
"similarity": 0.4199
},
{
"kra_text": "Provisions and manages cloud infrastructure on AWS, Azure, or GCP using Terraform or CloudFormation to enforce infrastructure-as-code standards.",
"sentence": "Good experience in Azure Services like DataLake, Azure SQL, Function App, Azure Cognitive Search.",
"similarity": 0.3791
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 10,
"score": 0.4477,
"slug": "devops-engineer",
"total_count": null
},
{
"display_name": "AI Compliance Officer",
"kra_matches": [
{
"kra_text": "Defines AI governance frameworks including fairness standards, transparency obligations, explainability requirements, and human oversight accountability structures.",
"sentence": "Different GenAI frameworks.. security and governance",
"similarity": 0.6469
},
{
"kra_text": "Maps AI system behaviors and data processing activities to regulatory requirements including EU AI Act, GDPR, CCPA, and sector-specific compliance frameworks.",
"sentence": "Good experience in Azure Services like DataLake, Azure SQL, Function App, Azure Cognitive Search.",
"similarity": 0.3807
},
{
"kra_text": "Maps AI system behaviors and data processing activities to regulatory requirements including EU AI Act, GDPR, CCPA, and sector-specific compliance frameworks.",
"sentence": "Good Understanding on Chunking, Embeddings, vectorization, indexing, Prompting, Hallucinations, RAG",
"similarity": 0.2837
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 12,
"score": 0.4371,
"slug": "ai-compliance-officer",
"total_count": null
},
{
"display_name": "AI Engineer",
"kra_matches": [
{
"kra_text": "Implements safety guardrails, content filtering, output validation, fallback handlers, and retry logic for robust and predictable AI feature behavior.",
"sentence": "Different GenAI frameworks.. security and governance",
"similarity": 0.4987
},
{
"kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
"sentence": "Good Understanding on Chunking, Embeddings, vectorization, indexing, Prompting, Hallucinations, RAG",
"similarity": 0.4138
},
{
"kra_text": "Documents AI feature capabilities, known limitations, failure modes, prompt versioning, and operational runbooks for engineering and product teams.",
"sentence": "Good experience in Azure Services like DataLake, Azure SQL, Function App, Azure Cognitive Search.",
"similarity": 0.3856
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 13,
"score": 0.4327,
"slug": "ai-engineer",
"total_count": null
},
{
"display_name": "Cloud Architect",
"kra_matches": [
{
"kra_text": "Defines cloud adoption roadmaps, lift-and-shift vs. refactor migration strategies, and landing zone architectures for workloads moving to AWS, Azure, or GCP.",
"sentence": "Good experience in Azure Services like DataLake, Azure SQL, Function App, Azure Cognitive Search.",
"similarity": 0.442
},
{
"kra_text": "Establishes cloud governance guardrails including budget alerts, resource quotas, policy-as-code enforcement, and compliance posture management.",
"sentence": "Different GenAI frameworks.. security and governance",
"similarity": 0.4407
},
{
"kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
"sentence": "Hands on experience in DevOps, create pull PRs and maintain code repositories.",
"similarity": 0.3815
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 9,
"score": 0.4214,
"slug": "cloud-architect",
"total_count": null
},
{
"display_name": ".NET Backend Developer",
"kra_matches": [
{
"kra_text": "backend code refactoring and maintenance",
"sentence": "Hands on experience in DevOps, create pull PRs and maintain code repositories.",
"similarity": 0.4541
},
{
"kra_text": "authentication and authorization support",
"sentence": "Different GenAI frameworks.. security and governance",
"similarity": 0.3881
},
{
"kra_text": "service-level technical collaboration",
"sentence": "Strong communication skills and ability to collaborate effectively with team members.",
"similarity": 0.3877
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 83,
"score": 0.41,
"slug": "dotnet-backend-developer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Fullstack Developer",
"kra_matches": null,
"matched_count": 5,
"matched_skills": [
"Azure",
"FastAPI",
"Python",
"REST",
"SQLAlchemy"
],
"role_id": 15,
"score": 0.8333,
"slug": "full-stack-engineer",
"total_count": 6
},
{
"display_name": "Python Backend Developer",
"kra_matches": null,
"matched_count": 5,
"matched_skills": [
"Azure",
"FastAPI",
"Python",
"REST",
"SQLAlchemy"
],
"role_id": 80,
"score": 0.8333,
"slug": "python-backend-developer",
"total_count": 6
},
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": 5,
"matched_skills": [
"Azure",
"FastAPI",
"Python",
"REST",
"SQLAlchemy"
],
"role_id": 1,
"score": 0.8333,
"slug": "backend-engineer",
"total_count": 6
},
{
"display_name": "Fullstack Developer",
"kra_matches": null,
"matched_count": 4,
"matched_skills": [
"FastAPI",
"Python",
"REST",
"SQLAlchemy"
],
"role_id": 435,
"score": 0.6667,
"slug": "fullstack-developer",
"total_count": 6
},
{
"display_name": "Node.js Backend Developer",
"kra_matches": null,
"matched_count": 4,
"matched_skills": [
"Azure",
"FastAPI",
"REST",
"SQLAlchemy"
],
"role_id": 82,
"score": 0.6667,
"slug": "node-backend-developer",
"total_count": 6
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "DOMAIN",
"chosen_role": {
"display_name": "LLM / GenAI Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 151,
"score": 0.97,
"slug": "llm-genai-engineer",
"total_count": null
},
"confidence": 0.97,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [
"GenAI application development",
"Azure-based backend integration",
"LLM retrieval-augmented generation",
"API and service integration",
"DevOps and code repository management",
"Security and governance for GenAI"
],
"matched_kras": [
"Strong experience in Python programming language - Must",
"Experience in REST APIs, Fast APIs, Graph APIs, SQL Alchemy",
"Good experience in Azure Services like DataLake, Azure SQL",
"Good experience in Azure Cognitive Search",
"Understanding on Chunking, Embeddings, vectorization, indexing",
"Understanding on Prompting, Hallucinations, RAG",
"Hands on experience in DevOps, create pull PRs and maintain code repositories",
"Different GenAI frameworks.. security and governance"
],
"matched_skills": [
"Python",
"REST APIs",
"Fast APIs",
"Graph APIs",
"SQL Alchemy",
"Azure DataLake",
"Azure SQL",
"Function App",
"Azure Cognitive Search",
"Chunking",
"Embeddings",
"vectorization",
"indexing",
"Prompting",
"RAG"
],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=AI / ML; The JD is centered on building GenAI applications with Python, Azure services, RAG, embeddings, prompting, and GenAI frameworks, which best matches an LLM/GenAI engineering role.",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 13,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": {
"best_kra_similarity": 0.0,
"queue_id": 1782,
"r_and_r_preview": "Gen AI, Python, Azure\n\n\u2022 Strong experience in Python programming language - Must.\n\u2022 Experience in REST APIs, Fast APIs, Graph APIs, SQL Alchemy.\n\u2022 Good experience in Azure Services like DataLake, Azur",
"role_display_name": "LLM / GenAI Engineer",
"role_slug": "llm-genai-engineer",
"status": "pending"
},
"new_skills_attached": [
{
"is_primary": false,
"queue_id": 23417,
"role_display_name": "LLM / GenAI Engineer",
"role_slug": "llm-genai-engineer",
"skill_name": "Graph API",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23418,
"role_display_name": "LLM / GenAI Engineer",
"role_slug": "llm-genai-engineer",
"skill_name": "Azure Data Lake",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23419,
"role_display_name": "LLM / GenAI Engineer",
"role_slug": "llm-genai-engineer",
"skill_name": "Azure SQL",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23420,
"role_display_name": "LLM / GenAI Engineer",
"role_slug": "llm-genai-engineer",
"skill_name": "Pull Requests",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23421,
"role_display_name": "LLM / GenAI Engineer",
"role_slug": "llm-genai-engineer",
"skill_name": "Code Repositories",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 23422,
"role_display_name": "LLM / GenAI Engineer",
"role_slug": "llm-genai-engineer",
"skill_name": "Generative AI",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23423,
"role_display_name": "LLM / GenAI Engineer",
"role_slug": "llm-genai-engineer",
"skill_name": "Chunking",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23424,
"role_display_name": "LLM / GenAI Engineer",
"role_slug": "llm-genai-engineer",
"skill_name": "Vectorization",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23425,
"role_display_name": "LLM / GenAI Engineer",
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"skill_name": "Hallucinations",
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}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
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"alias_persisted": false,
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"is_extractable": true,
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"matched_via": "alias"
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{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 407,
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"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
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"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
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"volatility": "STABLE"
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"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1837,
"existing_alias_text": "FastAPI",
"input_term": "FastAPI",
"matched_canonical": {
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"is_also_category": false,
"is_extractable": true,
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},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 156,
"existing_alias_text": "SQLAlchemy",
"input_term": "SQLAlchemy",
"matched_canonical": {
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"is_also_category": false,
"is_extractable": true,
"skill_nature": "LIBRARY",
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"matched_via": "alias"
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{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2357,
"existing_alias_text": "Azure Functions",
"input_term": "Azure Functions",
"matched_canonical": {
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"is_extractable": true,
"skill_nature": "CLOUD_SERVICE",
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"matched_via": "alias"
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{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 5892,
"existing_alias_text": "Azure Cognitive Search",
"input_term": "Azure Cognitive Search",
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"is_extractable": true,
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"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1852,
"existing_alias_text": "DevOps",
"input_term": "DevOps",
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"is_also_category": false,
"is_extractable": true,
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"typical_lifespan": "EVERGREEN",
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},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
"alias_persisted": false,
"existing_alias_id": 1872,
"existing_alias_text": "chunking strategies",
"input_term": "Chunking",
"matched_canonical": {
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"volatility": "EMERGING"
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"matched_via": "embedding_alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1831,
"existing_alias_text": "Embeddings",
"input_term": "Embeddings",
"matched_canonical": {
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"is_also_category": false,
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"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 148,
"existing_alias_text": "indexing",
"input_term": "Indexing",
"matched_canonical": {
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"is_extractable": true,
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},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1843,
"existing_alias_text": "Prompt engineering",
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"is_extractable": true,
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"volatility": "EMERGING"
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"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1871,
"existing_alias_text": "retrieval-augmented generation",
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"is_extractable": true,
"skill_nature": "PATTERN",
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"matched_via": "alias"
}
],
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{
"display_name": "Fullstack Developer",
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{
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},
{
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},
{
"display_name": "Data Engineer",
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"slug": "data-engineer",
"source": "db"
},
{
"display_name": "ML Engineer",
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"slug": "ml-engineer",
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},
{
"display_name": "MLOps Engineer",
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"slug": "ml-ops-engineer",
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},
{
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"slug": "ar-vr-engineer",
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},
{
"display_name": "Python Backend Developer",
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"role_archetype": "Engineering",
"slug": "python-backend-developer",
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},
{
"display_name": ".NET Backend Developer",
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},
{
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{
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"role_archetype": "Engineering",
"slug": "go-backend-developer",
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},
{
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"role_archetype": "Engineering",
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},
{
"display_name": "Kotlin Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
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{
"display_name": "Node.js Backend Developer",
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{
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},
{
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},
{
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},
{
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},
{
"display_name": "Ruby Backend Developer",
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"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
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},
{
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"slug": "pega-developer",
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},
{
"display_name": "Sitecore Dev",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"source": "db"
},
{
"display_name": "Web Developer",
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"role_archetype": null,
"slug": "web-developer",
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},
{
"display_name": "Drupal Dev",
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"rationale": null,
"role_archetype": "Engineering",
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}
],
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"display_name": "LLM / GenAI Engineer",
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"rationale": "Domain=AI / ML; The JD is centered on building GenAI applications with Python, Azure services, RAG, embeddings, prompting, and GenAI frameworks, which best matches an LLM/GenAI engineering role.",
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{
"dimension": {
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]
},
{
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]
},
{
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},
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},
{
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},
{
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]
},
{
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]
},
{
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},
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]
},
{
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},
{
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{
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{
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},
{
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{
"display_name": "Kotlin Backend Developer",
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{
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{
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{
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{
"display_name": "Scala Backend Developer",
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]
},
{
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"rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
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"input_skill": "Azure",
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{
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},
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{
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{
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{
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},
{
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{
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{
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{
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{
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{
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{
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]
},
{
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},
{
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{
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{
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{
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{
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{
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{
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},
{
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{
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{
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{
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{
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{
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},
{
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]
},
{
"dimension": {
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{
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{
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},
{
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{
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{
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{
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},
{
"dimension": {
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{
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{
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},
{
"dimension": {
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"dimension": {
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"slug": "d_init_02",
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},
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{
"dimension": {
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"rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
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},
"input_skill": "Indexing",
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"display_name": "Fullstack Developer",
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{
"display_name": "Fullstack Developer",
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"rationale": null,
"role_archetype": "Engineering",
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{
"display_name": "PHP Backend Developer",
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]
},
{
"dimension": {
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{
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{
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{
"display_name": "Python Backend Developer",
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"rationale": null,
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{
"display_name": "Ruby Backend Developer",
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{
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]
},
{
"dimension": {
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"rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
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"rationale": null,
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},
{
"display_name": "Sitecore Dev",
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]
},
{
"dimension": {
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"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Embeddings",
"llm_role": null,
"roles_from_db": []
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Systems Programming",
"id": 166,
"rationale": "Systems programming covers low-level software development where performance, memory safety, and direct control over resources matter. Rust fits here because it is commonly used for OS-adjacent services, infrastructure components, and other performance-sensitive systems code.",
"slug": "d_init_02",
"source": "db"
},
"input_skill": "Embeddings",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Embeddings",
"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": "Vectorization",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Machine Learning Frameworks",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "SHORT_LIVED",
"version_strategy": "VERSIONED",
"volatility": "FAST"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "vectorization",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "indexing",
"alias_type": "CANONICAL",
"id": 148,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "indexing",
"id": 20,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "indexing",
"sub_category_id": 2477,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Data Modeling",
"id": 216,
"rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
"slug": "relational-data-modeling",
"source": "db"
},
"input_skill": "Indexing",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 435,
"rationale": null,
"role_archetype": "Engineering",
"slug": "fullstack-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"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": "Indexing",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Search and Content Discovery",
"id": 356,
"rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
"slug": "search-and-content-discovery",
"source": "db"
},
"input_skill": "Indexing",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Drupal Dev",
"id": 228,
"rationale": null,
"role_archetype": "Engineering",
"slug": "drupal-dev",
"source": "db"
},
{
"display_name": "Sitecore Dev",
"id": 233,
"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"source": "db"
}
]
}
],
"input_skill": "Indexing",
"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": "Prompt engineering",
"alias_type": "CANONICAL",
"id": 1843,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "Prompt engineering",
"id": 1207,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "prompt-engineering",
"sub_category_id": 914,
"typical_lifespan": "EVERGREEN",
"volatility": "EMERGING"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Prompt Engineering",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Prompt Engineering",
"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": "Hallucinations",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Machine Learning Frameworks",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "SHORT_LIVED",
"version_strategy": "VERSIONED",
"volatility": "FAST"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "hallucinations",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "retrieval-augmented generation",
"alias_type": "CANONICAL",
"id": 1871,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 1,
"display_name": "retrieval-augmented generation",
"id": 1235,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PATTERN",
"slug": "retrieval-augmented-generation",
"sub_category_id": 930,
"typical_lifespan": "EVERGREEN",
"volatility": "EMERGING"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "RAG Architectures",
"id": 197,
"rationale": "Retrieval-augmented generation patterns that ground model responses in external knowledge. This cluster covers how to fetch, chunk, rank, and inject context so AI features answer from product data instead of hallucinating.",
"slug": "rag-architectures",
"source": "db"
},
"input_skill": "Retrieval-Augmented Generation",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
]
}
],
"input_skill": "Retrieval-Augmented Generation",
"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": [
"Graph API",
"Azure Data Lake",
"Azure SQL",
"Pull Requests",
"Code Repositories",
"Generative AI",
"Vectorization",
"Hallucinations"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "LLM / GenAI Engineer",
"id": 151,
"rationale": "Domain=AI / ML; The JD is centered on building GenAI applications with Python, Azure services, RAG, embeddings, prompting, and GenAI frameworks, which best matches an LLM/GenAI engineering role.",
"role_archetype": null,
"slug": "llm-genai-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "Azure",
"tag": "in_db"
},
{
"skill": "REST",
"tag": "in_db"
},
{
"skill": "FastAPI",
"tag": "in_db"
},
{
"skill": "Graph API",
"tag": "new"
},
{
"skill": "SQLAlchemy",
"tag": "in_db"
},
{
"skill": "Azure Data Lake",
"tag": "new"
},
{
"skill": "Azure SQL",
"tag": "new"
},
{
"skill": "Azure Functions",
"tag": "in_db"
},
{
"skill": "Azure Cognitive Search",
"tag": "in_db"
},
{
"skill": "DevOps",
"tag": "in_db"
},
{
"skill": "Pull Requests",
"tag": "new"
},
{
"skill": "Code Repositories",
"tag": "new"
},
{
"skill": "Generative AI",
"tag": "new"
},
{
"skill": "Chunking",
"tag": "in_db"
},
{
"skill": "Embeddings",
"tag": "in_db"
},
{
"skill": "Vectorization",
"tag": "new"
},
{
"skill": "Indexing",
"tag": "in_db"
},
{
"skill": "Prompt Engineering",
"tag": "in_db"
},
{
"skill": "Hallucinations",
"tag": "new"
},
{
"skill": "Retrieval-Augmented Generation",
"tag": "in_db"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 151,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Scripting \u0026 DSL Languages",
"id": 248,
"rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
"slug": "cloud-security-scripting-dsl-languages",
"source": "db"
},
"dimension_id": 248,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 151,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
"slug": "programming-languages",
"source": "db"
},
"dimension_id": 1,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 435,
"rationale": null,
"role_archetype": "Engineering",
"slug": "fullstack-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 151,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages \u0026 DSLs",
"id": 475,
"rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
"slug": "programming-languages-dsls",
"source": "db"
},
"dimension_id": 475,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 151,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"dimension_id": 59,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 151,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 151,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"dimension_id": 39,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 151,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for XR",
"id": 97,
"rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
"slug": "programming-languages-for-xr",
"source": "db"
},
"dimension_id": 97,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "AR/VR Engineer",
"id": 8,
"rationale": null,
"role_archetype": null,
"slug": "ar-vr-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 151,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Python Programming",
"id": 290,
"rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
"slug": "python-programming",
"source": "db"
},
"dimension_id": 290,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 151,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms",
"id": 20,
"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
"slug": "cloud-platforms",
"source": "db"
},
"dimension_id": 20,
"input_skill": "Azure",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
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{
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{
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{
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}
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},
{
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{
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{
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{
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},
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{
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}
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},
{
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"source": "db"
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{
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{
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{
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},
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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{
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"rationale": null,
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},
{
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},
{
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"source": "db"
},
"dimension_id": 477,
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{
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{
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},
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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{
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{
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{
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{
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},
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"roles_from_db": [
{
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{
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{
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{
"display_name": "PHP Backend Developer",
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{
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{
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{
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{
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{
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{
"display_name": "Sitecore Dev",
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{
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},
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"skill_id": 1201,
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{
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{
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{
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{
"display_name": "PHP Backend Developer",
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{
"display_name": "Python Backend Developer",
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}
],
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{
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"slug": "orms-and-data-access-layers",
"source": "db"
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"dimension_id": 5,
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"display_name": ".NET Backend Developer",
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{
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{
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{
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{
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{
"display_name": "PHP Backend Developer",
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{
"display_name": "Python Backend Developer",
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{
"display_name": "Ruby Backend Developer",
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{
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"display_name": "Cloud Platforms \u0026 Hosting Providers",
"id": 278,
"rationale": "Familiarity with vendor-specific hosting and backend services for deploying and scaling web applications.",
"slug": "cloud-platforms-hosting-providers",
"source": "db"
},
"dimension_id": 278,
"input_skill": "Azure Functions",
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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{
"display_name": ".NET Backend Developer",
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{
"display_name": "Kotlin Backend Developer",
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{
"display_name": "Scala Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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{
"display_name": "Web Developer",
"id": 25,
"rationale": null,
"role_archetype": null,
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],
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"skill_id": 1462,
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{
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"source": "db"
},
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{
"display_name": "Go Backend Developer",
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{
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{
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"dimension": {
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"display_name": "Search and Content Discovery",
"id": 356,
"rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
"slug": "search-and-content-discovery",
"source": "db"
},
"dimension_id": 356,
"input_skill": "Azure Cognitive Search",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Drupal Dev",
"id": 228,
"rationale": null,
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"slug": "drupal-dev",
"source": "db"
},
{
"display_name": "Sitecore Dev",
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"role_archetype": "Engineering",
"slug": "sitecore-dev",
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}
],
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"skill_id": 4169,
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},
{
"chosen_role_id": 151,
"dimension": {
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"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"
},
"dimension_id": 150,
"input_skill": "DevOps",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
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],
"skill_dimension_saved": true,
"skill_id": 1216,
"skill_tag": "in_db",
"skipped_reason": null
},
{
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