Pipeline run
2c6fc815-c1c2-4044-88b0-ff0560956cbd
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
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Data Engineer
CASE Aslug: data-engineer · id: 2 · source: db
Exact alias hit on data-engineer (1.0) — no other alias at this confidence; skill_top ai-engineer 0.14 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Job Title: Software Engineer Skills : Data Bricks, AI on Azure, Synapse Experience Required: - 5 to 8 years Location : Noida Job Summary: We are seeking a highly skilled and motivated Software Engineer with expertise in DataBricks, AI on Azure, and Synapse to join our dynamic team. As a Software Engineer, you will play a pivotal role in designing, developing, and maintaining data-driven solutions and AI applications on the Azure platform, leveraging cutting-edge technologies to drive innovation and business growth. Key Responsibilities: • Design and Development: Collaborate with cross-functional teams to design and develop robust, scalable, and efficient software solutions using DataBricks, AI services on Azure, and Synapse. • Data Engineering: Work with large datasets, perform data wrangling, and develop data pipelines to support AI and analytics initiatives. • Machine Learning: Develop, implement, and optimize machine learning models for various use cases, such as predictive analytics, natural language processing, computer vision, and more. • Azure Services: Utilize Azure services such as Azure Machine Learning, Azure Data Factory, Azure Synapse Analytics, and Azure DevOps to build end-to-end data and AI solutions. • Code Quality and Testing: Write clean, maintainable code and conduct thorough testing to ensure the reliability and accuracy of software applications. • Performance Optimization: Identify performance bottlenecks and optimize code and processes for enhanced system performance and efficiency. • Collaboration: Collaborate effectively with data scientists, data engineers, and other team members to achieve project goals and deliverables. • Documentation: Create and maintain technical documentation, including design documents, code comments, and user guides. • Security and Compliance: Ensure that software solutions adhere to security best practices and compliance requirements. • Continuous Learning: Stay updated with the latest advancements in AI, Azure, and Data Bricks technologies and integrate them into projects when appropriate.
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
- Databricks (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Data Analytics Platform
- Vendor
- Databricks, Inc.
- License
- other_open
- Year introduced
- 2013
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Databricks appears frequently in data engineering and analytics job postings, especially alongside Spark, Delta Lake, and lakehouse stacks; strong vendor adoption and broad enterprise usage signal mainstream demand.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 911
- 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) |
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 saved |
|
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Machine Learning (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Machine Learning
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Machine Learning appears in large volumes of job descriptions across data, product, and platform roles, and major cloud vendors (AWS, Google Cloud, Azure) offer dedicated ML services and certifications, indicating broad adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1024
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
AI Governance and Model Security Catalog dimension db id 50
Library dimension (catalog)
Roles linked in library: AI Engineer, ML Engineer, MLOps Engineer
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
AI Governance and Model Security
ai-governance-and-model-security
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Azure ML (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Ml Platform
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2018
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Azure ML appears frequently in ML/DS job postings and Microsoft’s Azure AI portfolio, indicating broad enterprise adoption for model training and deployment on Azure.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 175
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
MLOps Platforms and Lifecycle Catalog dimension db id 43
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Azure Synapse Analytics (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Analytics Service
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2019
- Confidence
- 0.95
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common in cloud data-platform JDs and Microsoft’s Azure analytics stack; often listed alongside Databricks/ADF for warehousing and ETL, indicating broad hiring demand.
Skill profile (library / DB)
- Skill nature
- CLOUD_SERVICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 117
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Data Warehouses Catalog dimension db id 22
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Data Warehouses
cloud-data-warehouses
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- Azure DevOps (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Devops Platform
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2018
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Azure DevOps appears in many enterprise job descriptions for CI/CD, boards, and repos, and Microsoft continues active product support and updates; it remains a common hiring-pipeline skill alongside GitHub Actions/Jenkins.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 170
- 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
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- 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
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- AI (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Artificial Intelligence
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: AI appears in a large and growing share of job descriptions across software, data, and product roles; major vendors like Microsoft, Google, and AWS have broad AI offerings and hiring demand reflects mainstream adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1020
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering 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
- Data Engineering 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
- Testing Tools
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| Databricks | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| 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) | |
| Machine Learning | in_db |
AI Governance and Model Security
ai-governance-and-model-security
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Machine Learning | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure Machine Learning | new |
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Azure Synapse Analytics | in_db |
Cloud Data Warehouses
cloud-data-warehouses
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Azure DevOps | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AI | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Synapse | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Azure Data Factory | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Natural Language Processing | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Computer Vision | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Pipelines | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Wrangling | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Testing | type=Testing Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| dimension_skill_link_proposed | Azure Machine Learning ↔ MLOps Platforms and Lifecycle |
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": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": 8,
"min": 5,
"raw": "5 to 8 years"
},
"job_locations": [
{
"aliases": [],
"city": "Noida",
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "Software Engineer",
"role_aliases": [
"Software Developer",
"SWE",
"Data Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 10,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Key Responsibilities: \u2022 Design and",
"last_5_words": "integrate them into projects when"
},
"text": "\u2022 Design and Development: Collaborate with cross-functional teams to design and develop robust, scalable, and efficient software solutions using DataBricks, AI services on Azure, and Synapse.\n\n\u2022 Data Engineering: Work with large datasets, perform data wrangling, and develop data pipelines to support AI and analytics initiatives.\n\n\u2022 Machine Learning: Develop, implement, and optimize machine learning models for various use cases, such as predictive analytics, natural language processing, computer vision, and more.\n\n\u2022 Azure Services: Utilize Azure services such as Azure Machine Learning, Azure Data Factory, Azure Synapse Analytics, and Azure DevOps to build end-to-end data and AI solutions.\n\n\u2022 Code Quality and Testing: Write clean, maintainable code and conduct thorough testing to ensure the reliability and accuracy of software applications.\n\n\u2022 Performance Optimization: Identify performance bottlenecks and optimize code and processes for enhanced system performance and efficiency.\n\n\u2022 Collaboration: Collaborate effectively with data scientists, data engineers, and other team members to achieve project goals and deliverables.\n\n\u2022 Documentation: Create and maintain technical documentation, including design documents, code comments, and user guides.\n\n\u2022 Security and Compliance: Ensure that software solutions adhere to security best practices and compliance requirements.\n\n\u2022 Continuous Learning: Stay updated with the latest advancements in AI, Azure, and Data Bricks technologies and integrate them into projects when appropriate.",
"word_count": 284
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Databricks"
},
{
"is_primary": true,
"skill_name": "Azure"
},
{
"is_primary": true,
"skill_name": "Synapse"
},
{
"is_primary": true,
"skill_name": "Machine Learning"
},
{
"is_primary": true,
"skill_name": "Azure Machine Learning"
},
{
"is_primary": true,
"skill_name": "Azure Data Factory"
},
{
"is_primary": true,
"skill_name": "Azure Synapse Analytics"
},
{
"is_primary": true,
"skill_name": "Azure DevOps"
},
{
"is_primary": true,
"skill_name": "Natural Language Processing"
},
{
"is_primary": true,
"skill_name": "Computer Vision"
},
{
"is_primary": true,
"skill_name": "AI"
},
{
"is_primary": true,
"skill_name": "Data Pipelines"
},
{
"is_primary": true,
"skill_name": "Data Wrangling"
},
{
"is_primary": true,
"skill_name": "Testing"
}
],
"jd_role": {
"display_name": "Software Engineer",
"rationale": null,
"role_aliases": [
"Software Developer",
"SWE",
"Data Engineer"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": 8,
"min": 5,
"raw": "5 to 8 years"
},
"job_locations": [
{
"aliases": [],
"city": "Noida",
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "Software Engineer",
"role_aliases": [
"Software Developer",
"SWE",
"Data Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 10,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Key Responsibilities: \u2022 Design and",
"last_5_words": "integrate them into projects when"
},
"text": "\u2022 Design and Development: Collaborate with cross-functional teams to design and develop robust, scalable, and efficient software solutions using DataBricks, AI services on Azure, and Synapse.\n\n\u2022 Data Engineering: Work with large datasets, perform data wrangling, and develop data pipelines to support AI and analytics initiatives.\n\n\u2022 Machine Learning: Develop, implement, and optimize machine learning models for various use cases, such as predictive analytics, natural language processing, computer vision, and more.\n\n\u2022 Azure Services: Utilize Azure services such as Azure Machine Learning, Azure Data Factory, Azure Synapse Analytics, and Azure DevOps to build end-to-end data and AI solutions.\n\n\u2022 Code Quality and Testing: Write clean, maintainable code and conduct thorough testing to ensure the reliability and accuracy of software applications.\n\n\u2022 Performance Optimization: Identify performance bottlenecks and optimize code and processes for enhanced system performance and efficiency.\n\n\u2022 Collaboration: Collaborate effectively with data scientists, data engineers, and other team members to achieve project goals and deliverables.\n\n\u2022 Documentation: Create and maintain technical documentation, including design documents, code comments, and user guides.\n\n\u2022 Security and Compliance: Ensure that software solutions adhere to security best practices and compliance requirements.\n\n\u2022 Continuous Learning: Stay updated with the latest advancements in AI, Azure, and Data Bricks technologies and integrate them into projects when appropriate.",
"word_count": 284
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "2c6fc815-c1c2-4044-88b0-ff0560956cbd",
"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
}
],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Data Engineering: Work with large datasets, perform data wrangling, and develop data pipelines to support AI and analytics initiatives.",
"similarity": 0.6226
},
{
"kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
"sentence": "Design and Development: Collaborate with cross-functional teams to design and develop robust, scalable, and efficient software solutions using DataBricks, AI services on Azure, and Synapse.",
"similarity": 0.5708
},
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Collaboration: Collaborate effectively with data scientists, data engineers, and other team members to achieve project goals and deliverables.",
"similarity": 0.5545
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.5827,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
"kra_text": "optimize responsiveness and performance",
"sentence": "Performance Optimization: Identify performance bottlenecks and optimize code and processes for enhanced system performance and efficiency.",
"similarity": 0.6077
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Collaboration: Collaborate effectively with data scientists, data engineers, and other team members to achieve project goals and deliverables.",
"similarity": 0.5665
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Design and Development: Collaborate with cross-functional teams to design and develop robust, scalable, and efficient software solutions using DataBricks, AI services on Azure, and Synapse.",
"similarity": 0.5614
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.5785,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "Go Backend Developer",
"kra_matches": [
{
"kra_text": "performance tuning and resource efficiency",
"sentence": "Performance Optimization: Identify performance bottlenecks and optimize code and processes for enhanced system performance and efficiency.",
"similarity": 0.6178
},
{
"kra_text": "code review and testing support",
"sentence": "Code Quality and Testing: Write clean, maintainable code and conduct thorough testing to ensure the reliability and accuracy of software applications.",
"similarity": 0.5917
},
{
"kra_text": "code review and testing support",
"sentence": "Documentation: Create and maintain technical documentation, including design documents, code comments, and user guides.",
"similarity": 0.4264
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 81,
"score": 0.5453,
"slug": "go-backend-developer",
"total_count": null
},
{
"display_name": "ML Engineer",
"kra_matches": [
{
"kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
"sentence": "Data Engineering: Work with large datasets, perform data wrangling, and develop data pipelines to support AI and analytics initiatives.",
"similarity": 0.56
},
{
"kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
"sentence": "Machine Learning: Develop, implement, and optimize machine learning models for various use cases, such as predictive analytics, natural language processing, computer vision, and more.",
"similarity": 0.5364
},
{
"kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
"sentence": "Azure Services: Utilize Azure services such as Azure Machine Learning, Azure Data Factory, Azure Synapse Analytics, and Azure DevOps to build end-to-end data and AI solutions.",
"similarity": 0.5019
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 3,
"score": 0.5328,
"slug": "ml-engineer",
"total_count": null
},
{
"display_name": "Java Backend Developer",
"kra_matches": [
{
"kra_text": "backend performance tuning",
"sentence": "Performance Optimization: Identify performance bottlenecks and optimize code and processes for enhanced system performance and efficiency.",
"similarity": 0.6321
},
{
"kra_text": "code refactoring and defect fixes",
"sentence": "Code Quality and Testing: Write clean, maintainable code and conduct thorough testing to ensure the reliability and accuracy of software applications.",
"similarity": 0.4929
},
{
"kra_text": "service contract collaboration",
"sentence": "Collaboration: Collaborate effectively with data scientists, data engineers, and other team members to achieve project goals and deliverables.",
"similarity": 0.4546
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 79,
"score": 0.5265,
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"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "AI Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Azure",
"Machine Learning"
],
"role_id": 13,
"score": 0.1429,
"slug": "ai-engineer",
"total_count": 14
},
{
"display_name": "ML Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Azure",
"Machine Learning"
],
"role_id": 3,
"score": 0.1429,
"slug": "ml-engineer",
"total_count": 14
},
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Azure",
"Azure Synapse Analytics"
],
"role_id": 2,
"score": 0.1429,
"slug": "data-engineer",
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},
{
"display_name": "DevOps Engineer",
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"matched_count": 2,
"matched_skills": [
"Azure",
"Azure DevOps"
],
"role_id": 10,
"score": 0.1429,
"slug": "devops-engineer",
"total_count": 14
},
{
"display_name": "MLOps Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Azure",
"Machine Learning"
],
"role_id": 16,
"score": 0.1429,
"slug": "ml-ops-engineer",
"total_count": 14
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
"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
},
"confidence": 1.0,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [],
"matched_kras": [],
"matched_skills": [],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top ai-engineer 0.14 does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 517,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 24441,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Synapse",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24442,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Azure Machine Learning",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24443,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Azure Data Factory",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24444,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Natural Language Processing",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24445,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Computer Vision",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24446,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Pipelines",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24447,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Wrangling",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24448,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Testing",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
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{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1838,
"existing_alias_text": "Databricks",
"input_term": "Databricks",
"matched_canonical": {
"category_id": 9,
"display_name": "Databricks",
"id": 1202,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "databricks",
"sub_category_id": 911,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 407,
"existing_alias_text": "Azure",
"input_term": "Azure",
"matched_canonical": {
"category_id": 9,
"display_name": "Azure",
"id": 188,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "azure",
"sub_category_id": 46,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2015,
"existing_alias_text": "Machine Learning",
"input_term": "Machine Learning",
"matched_canonical": {
"category_id": 2,
"display_name": "Machine Learning",
"id": 1356,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "machine-learning",
"sub_category_id": 1024,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
"alias_persisted": false,
"existing_alias_id": 464,
"existing_alias_text": "Azure ML",
"input_term": "Azure Machine Learning",
"matched_canonical": {
"category_id": 9,
"display_name": "Azure ML",
"id": 212,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "azure-ml",
"sub_category_id": 175,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "embedding_alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 302,
"existing_alias_text": "Azure Synapse Analytics",
"input_term": "Azure Synapse Analytics",
"matched_canonical": {
"category_id": 11,
"display_name": "Azure Synapse Analytics",
"id": 108,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CLOUD_SERVICE",
"slug": "azure-synapse-analytics",
"sub_category_id": 117,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1850,
"existing_alias_text": "Azure DevOps",
"input_term": "Azure DevOps",
"matched_canonical": {
"category_id": 9,
"display_name": "Azure DevOps",
"id": 1214,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "azure-devops",
"sub_category_id": 170,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1990,
"existing_alias_text": "AI",
"input_term": "AI",
"matched_canonical": {
"category_id": 2,
"display_name": "AI",
"id": 1347,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "ai",
"sub_category_id": 1020,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
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"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
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},
{
"display_name": "Backend Developer",
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"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
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"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
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"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",
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"rationale": null,
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"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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"source": "db"
},
{
"display_name": "Scala Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
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},
{
"display_name": "AI Engineer",
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"slug": "ai-engineer",
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},
{
"display_name": "Cloud Architect",
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"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "Cloud Security Engineer",
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"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Engineering Manager",
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"slug": "engineering-manager",
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}
],
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top ai-engineer 0.14 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"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": "Databricks",
"llm_role": null,
"roles_from_db": []
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms",
"id": 20,
"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
"slug": "cloud-platforms",
"source": "db"
},
"input_skill": "Azure",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
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"role_archetype": "Engineering",
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"source": "db"
},
{
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"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
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"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
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"slug": "data-engineer",
"source": "db"
},
{
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},
{
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},
{
"display_name": "Go Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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},
{
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"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
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"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
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"rationale": null,
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"slug": "ml-engineer",
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},
{
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"slug": "ml-ops-engineer",
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},
{
"display_name": "Node.js Backend Developer",
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"role_archetype": "Engineering",
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"source": "db"
},
{
"display_name": "Python Backend Developer",
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"rationale": null,
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"slug": "python-backend-developer",
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},
{
"display_name": "Scala Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"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.",
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"source": "db"
},
"input_skill": "Azure",
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"roles_from_db": [
{
"display_name": "Fullstack Developer",
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},
{
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},
{
"display_name": "Node.js Backend Developer",
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"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
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"rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
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},
"input_skill": "Azure",
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"roles_from_db": [
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]
},
{
"dimension": {
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"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.",
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"source": "db"
},
"input_skill": "Azure",
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"roles_from_db": [
{
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{
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}
]
},
{
"dimension": {
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"display_name": "Cloud Security Posture Tools",
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"rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
"slug": "cloud-security-posture-tools",
"source": "db"
},
"input_skill": "Azure",
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"roles_from_db": [
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{
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]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Vendor Product Families",
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"rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
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"source": "db"
},
"input_skill": "Azure",
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"roles_from_db": [
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]
},
{
"dimension": {
"difficulty_hint": "well_known",
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{
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"skill_nature": "CONCEPT",
"slug": "ai",
"sub_category_id": 1020,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "AI",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "AI",
"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": "Data Pipelines",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "PRACTICE",
"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": "data-pipelines",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Data Wrangling",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "PRACTICE",
"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": "data-wrangling",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Testing",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Testing Tools",
"skill_nature": "PRACTICE",
"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": "testing",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Synapse",
"Azure Data Factory",
"Natural Language Processing",
"Computer Vision",
"Data Pipelines",
"Data Wrangling",
"Testing"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top ai-engineer 0.14 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Databricks",
"tag": "in_db"
},
{
"skill": "Azure",
"tag": "in_db"
},
{
"skill": "Synapse",
"tag": "new"
},
{
"skill": "Machine Learning",
"tag": "in_db"
},
{
"skill": "Azure Machine Learning",
"tag": "in_db"
},
{
"skill": "Azure Data Factory",
"tag": "new"
},
{
"skill": "Azure Synapse Analytics",
"tag": "in_db"
},
{
"skill": "Azure DevOps",
"tag": "in_db"
},
{
"skill": "Natural Language Processing",
"tag": "new"
},
{
"skill": "Computer Vision",
"tag": "new"
},
{
"skill": "AI",
"tag": "in_db"
},
{
"skill": "Data Pipelines",
"tag": "new"
},
{
"skill": "Data Wrangling",
"tag": "new"
},
{
"skill": "Testing",
"tag": "new"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 2,
"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"
},
"dimension_id": 96,
"input_skill": "Databricks",
"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": [],
"skill_dimension_saved": true,
"skill_id": 1202,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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"
},
"dimension_id": 221,
"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": "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": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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"
},
"dimension_id": 211,
"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": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Provider Platforms",
"id": 131,
"rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
"slug": "cloud-provider-platforms",
"source": "db"
},
"dimension_id": 131,
"input_skill": "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": "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"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Posture Tools",
"id": 64,
"rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
"slug": "cloud-security-posture-tools",
"source": "db"
},
"dimension_id": 64,
"input_skill": "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": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Vendor Product Families",
"id": 477,
"rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
"slug": "vendor-product-families",
"source": "db"
},
"dimension_id": 477,
"input_skill": "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": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "AI Governance and Model Security",
"id": 50,
"rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
"slug": "ai-governance-and-model-security",
"source": "db"
},
"dimension_id": 50,
"input_skill": "Machine Learning",
"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": "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"
}
],
"skill_dimension_saved": true,
"skill_id": 1356,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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"
},
"dimension_id": 96,
"input_skill": "Machine Learning",
"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": [],
"skill_dimension_saved": true,
"skill_id": 1356,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "MLOps Platforms and Lifecycle",
"id": 43,
"rationale": "End-to-end managed platforms used to train, deploy, register, and govern models across their lifecycle. This is the operational control plane for production ML workflows.",
"slug": "mlops-platforms-and-lifecycle",
"source": "db"
},
"dimension_id": 43,
"input_skill": "Azure Machine Learning",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "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": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Data Warehouses",
"id": 22,
"rationale": "Managed analytical storage and compute platforms used for curated datasets, reporting, and downstream analytics. These systems are central to data modeling, performance tuning, and cost-aware query design.",
"slug": "cloud-data-warehouses",
"source": "db"
},
"dimension_id": 22,
"input_skill": "Azure Synapse Analytics",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 108,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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"
},
"dimension_id": 150,
"input_skill": "Azure 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",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1214,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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"
},
"dimension_id": 96,
"input_skill": "AI",
"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": [],
"skill_dimension_saved": true,
"skill_id": 1347,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 1
},
"planner_output": null,
"run_id": "2c6fc815-c1c2-4044-88b0-ff0560956cbd"
}