Pipeline run
e5e6842a-9a1e-457e-9159-d70fb220cbf8
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
The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optim…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Backend Developer
CASE Aslug: backend-engineer · id: 1 · source: db
Exact alias hit on backend-engineer (1.0) — no other alias at this confidence; skill_top backend-engineer 0.40 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Job Description The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to: Backend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day). Integrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc.) Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s). AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale. Distributed cloud architecture: Apply serverless and container based technologies in a micro-services environment to develop highly scalable backend codes. Agile development: Follow agile development processes to achieve impactful outcomes. Candidate Profile Entrepreneurial mind set with a positive attitude is a must. Prior experience (minimum 2 years) in backend development. Expert knowledge of new generation technologies is a must (e.g. Machine Queues, MSA architecture, PWA architecture, No-SQL, Serverless, Redis, Python, Django, SQL, Docker/Containers/Kubernetes, etc.). Strong acumen in algorithmic problem solving. Self-learner: highly curious, self-starter and can work with minimum supervision and guidance. Track record of excellence in academics or non-academic areas, with significant accomplishments. Excellent written & oral communication and inter-personal skills, with high degree of comfort working in teams and making teams successful. Qualifications BTech / BE / BS / MTech / MCA / ME / MS in Computer Science/Engineering, IT or related field 2 - 5 years work experience. (ref:hirist.com)
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
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 saved |
|
Programming Languages & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Django (CANONICAL) primary
- Django 1 (VERSION)
- Django 1.x (VERSION)
- Django 2 (VERSION)
- Django 2.x (VERSION)
- Django 3 (VERSION)
- Django 3.x (VERSION)
- Django 4 (VERSION)
- Django 4.x (VERSION)
- Django 5 (VERSION)
- Django 5.x (VERSION)
- Django1 (VERSION)
- Django2 (VERSION)
- Django3 (VERSION)
- Django4 (VERSION)
- Django5 (VERSION)
- django 2 (VERSION)
- django 2.x (VERSION)
- django 3 (VERSION)
- django 3.x (VERSION)
- django 4 (VERSION)
- django 4.x (VERSION)
- django 5 (VERSION)
- django 5.0 (VERSION)
- django 5.x (VERSION)
- django2 (VERSION)
- django2.x (VERSION)
- django3 (VERSION)
- django3.x (VERSION)
- django4 (VERSION)
- django4.x (VERSION)
- django5 (VERSION)
- django5.0 (VERSION)
- django5.x (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Web Framework
- Vendor
- Django Software Foundation
- License
- bsd
- Year introduced
- 2005
- Confidence
- 0.99
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 5
Maturity reasoning: Django appears in many backend web job descriptions and remains a standard Python web framework; its GitHub ecosystem and long-term LTS releases show sustained market demand.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 35
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Frameworks & Libraries Catalog dimension db id 360
Library dimension (catalog)
Roles linked in library: Drupal Dev, Engineering Manager
-
Web Application Frameworks Catalog dimension db id 2
Library dimension (catalog)
Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer, Java Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Frameworks & Libraries
frameworks-libraries
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Web Application Frameworks
web-application-frameworks
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- SQL (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Query Language
- Vendor
- ANSI
- License
- unknown
- Year introduced
- 1974
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 97
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Pega Programming Languages & DSLs Catalog dimension db id 267
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Programming Languages & DSLs Catalog dimension db id 475
Library dimension (catalog)
Roles linked in library: Engineering Manager
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Docker (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Containerization Tool
- Vendor
- Docker, Inc.
- License
- apache_2
- Year introduced
- 2013
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Docker is a hiring-pipeline staple: it appears in many DevOps, backend, and platform JDs, and remains a standard containerization tool alongside Kubernetes in production stacks.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 63
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Containerization and Image Builds Catalog dimension db id 152
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Deployment and Cloud Platforms Catalog dimension db id 418
Library dimension (catalog)
Roles linked in library: Ruby Backend Developer
-
Deployment and Runtime Configuration Catalog dimension db id 13
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Go Backend Developer, PHP Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Containerization and Image Builds
containerization-and-image-builds
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Cloud Platforms
deployment-and-cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Runtime Configuration
deployment-and-runtime-configuration
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- Kubernetes (CANONICAL) primary
- Kubernetes 1.0+ (VERSION)
- Kubernetes 1.x (VERSION)
- Kubernetes v1 (VERSION)
- k8s (VERSION)
- kubernetes 1.x (VERSION)
- kubernetes latest (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Container Orchestration Platform
- Vendor
- Cloud Native Computing Foundation
- License
- apache_2
- Year introduced
- 2014
- Confidence
- 0.90
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 1.30
Maturity reasoning: Broadly adopted in cloud-native stacks; Kubernetes appears in a large share of DevOps/SRE job descriptions and is the default orchestration platform across major cloud vendors.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 557
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Container Orchestration Platforms Catalog dimension db id 134
Library dimension (catalog)
Roles linked in library: Cloud Architect, DevOps Engineer
-
Kubernetes for ML Workloads Catalog dimension db id 47
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Container Orchestration Platforms
container-orchestration-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Redis (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Key Value Store
- Vendor
- Redis Labs
- License
- apache_2
- Year introduced
- 2009
- Confidence
- 0.95
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Redis appears in many job descriptions for caching, queues, and session storage, and is a standard datastore in modern backend stacks; vendor activity and broad ecosystem support indicate strong market demand.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 28
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Caching and State Management Catalog dimension db id 7
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
-
Magento Caching and Performance Catalog dimension db id 404
Library dimension (catalog)
Roles linked in library: Magento Dev
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Caching and State Management
caching-and-state-management
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Magento Caching and Performance
magento-caching-and-performance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Agile (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Agile
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 3594
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
-
Software Concepts, Patterns & Practices Catalog dimension db id 478
Library dimension (catalog)
Roles linked in library: Engineering Manager
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Serverless Framework (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Infrastructure As Code Framework
- Vendor
- Serverless, Inc.
- License
- mit
- Year introduced
- 2015
- Confidence
- 0.95
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Commonly listed in cloud/IaC job descriptions for AWS Lambda deployments; strong GitHub usage and vendor ecosystem support indicate broad adoption, though often alongside newer tools like SST/CDK.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 145
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Infrastructure as Code Catalog dimension db id 132
Library dimension (catalog)
Roles linked in library: Cloud Architect, DevOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Infrastructure as Code
infrastructure-as-code
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Aliases — catalog
- microservices (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Architecture
- Sub-category
- Distributed System Architecture
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Microservices is a common architecture in job descriptions across backend/cloud roles, and major vendors like AWS, Google Cloud, and Kubernetes ecosystems provide first-class support and reference patterns.
Skill profile (library / DB)
- Skill nature
- PATTERN
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 1
- Sub-category id
- 1
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Microservices and Distributed Systems Catalog dimension db id 9
Library dimension (catalog)
Roles linked in library: Backend Developer, Node.js Backend Developer, Scala Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Microservices and Distributed Systems
microservices-and-distributed-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- NoSQL (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Database Paradigm
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: NoSQL is broadly listed in job descriptions across backend/data roles, with MongoDB, DynamoDB, and Cassandra appearing as common market signals; it remains a hiring-pipeline staple rather than a niche or sunset tech.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1019
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
NoSQL Databases Catalog dimension db id 19
Library dimension (catalog)
Roles linked in library: Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
NoSQL Databases
nosql-databases
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- Artificial Intelligence (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, and major vendors (Microsoft, Google, AWS) have standardized AI offerings, signaling broad market adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1020
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
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
- API (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Application Programming Interface
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: APIs are a core requirement in most software engineering JDs and underpin common integrations across cloud, mobile, and web stacks; major vendors like AWS, Stripe, and Google Cloud center products on API-first usage.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1174
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
API Integration and Data Fetching Catalog dimension db id 127
Library dimension (catalog)
Roles linked in library: Angular Frontend Developer, Frontend Developer, Fullstack Developer, Fullstack Developer, React Frontend Developer, Svelte Frontend Developer, Vue Frontend Developer, Web Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
API Integration and Data Fetching
api-integration-and-data-fetching
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- 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
- DevOps Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| Python | in_db |
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages
programming-languages
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Python | in_db |
Programming Languages & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Django | in_db |
Frameworks & Libraries
frameworks-libraries
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Django | in_db |
Web Application Frameworks
web-application-frameworks
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| SQL | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL | in_db |
Programming Languages & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Containerization and Image Builds
containerization-and-image-builds
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Deployment and Cloud Platforms
deployment-and-cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Deployment and Runtime Configuration
deployment-and-runtime-configuration
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Kubernetes | in_db |
Container Orchestration Platforms
container-orchestration-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kubernetes | in_db |
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Redis | in_db |
Caching and State Management
caching-and-state-management
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Redis | in_db |
Magento Caching and Performance
magento-caching-and-performance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Agile | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Agile | in_db |
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Serverless | new |
Infrastructure as Code
infrastructure-as-code
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Microservices | in_db |
Microservices and Distributed Systems
microservices-and-distributed-systems
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| NoSQL | in_db |
NoSQL Databases
nosql-databases
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Artificial Intelligence | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Machine Learning | in_db |
AI Governance and Model Security
ai-governance-and-model-security
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Machine Learning | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| API | in_db |
API Integration and Data Fetching
api-integration-and-data-fetching
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | SaaS | type=Cloud Platforms subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Containerization | type=DevOps Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| dimension_skill_link_proposed | Serverless ↔ Infrastructure as Code |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [
"SaaS",
"Software Products"
],
"domain": "Software \u0026 SaaS Products"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE/BSC - Computer Science/Engineering (or related)",
"raw": "BTech / BE / BS / MTech / MCA / ME / MS in Computer Science/Engineering, IT or related field",
"requirement": "required"
}
],
"experience": {
"max": 5,
"min": 2,
"raw": "2 - 5 years work experience"
},
"job_locations": [],
"role": "Backend Developer",
"role_aliases": [
"Software Engineer",
"Backend Engineer",
"SDE"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 6,
"heading": "Job Description",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The primary role of the",
"last_5_words": "achieve impactful outcomes."
},
"text": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to:\n\nBackend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).\nIntegrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc.)\nData engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).\nAI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.\nDistributed cloud architecture: Apply serverless and container based technologies in a micro-services environment to develop highly scalable backend codes.\nAgile development: Follow agile development processes to achieve impactful outcomes.",
"word_count": 174
},
{
"bullet_count": 7,
"heading": "Candidate Profile",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Entrepreneurial mind set with",
"last_5_words": "making teams successful."
},
"text": "Entrepreneurial mind set with a positive attitude is a must.\nPrior experience (minimum 2 years) in backend development.\nExpert knowledge of new generation technologies is a must (e.g. Machine Queues, MSA architecture, PWA architecture, No-SQL, Serverless, Redis, Python, Django, SQL, Docker/Containers/Kubernetes, etc.).\nStrong acumen in algorithmic problem solving.\nSelf-learner: highly curious, self-starter and can work with minimum supervision and guidance.\nTrack record of excellence in academics or non-academic areas, with significant accomplishments.\nExcellent written \u0026 oral communication and inter-personal skills, with high degree of comfort working in teams and making teams successful.",
"word_count": 104
}
],
"urls": [
{
"type": "other",
"url": "https://hirist.com"
}
]
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Python"
},
{
"is_primary": true,
"skill_name": "Django"
},
{
"is_primary": true,
"skill_name": "SQL"
},
{
"is_primary": true,
"skill_name": "Docker"
},
{
"is_primary": true,
"skill_name": "Kubernetes"
},
{
"is_primary": true,
"skill_name": "Redis"
},
{
"is_primary": true,
"skill_name": "Agile"
},
{
"is_primary": true,
"skill_name": "Serverless"
},
{
"is_primary": true,
"skill_name": "Microservices"
},
{
"is_primary": true,
"skill_name": "NoSQL"
},
{
"is_primary": true,
"skill_name": "Artificial Intelligence"
},
{
"is_primary": true,
"skill_name": "Machine Learning"
},
{
"is_primary": true,
"skill_name": "API"
},
{
"is_primary": true,
"skill_name": "SaaS"
},
{
"is_primary": true,
"skill_name": "Containerization"
}
],
"jd_role": {
"display_name": "Backend Developer",
"rationale": null,
"role_aliases": [
"Software Engineer",
"Backend Engineer",
"SDE"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [
"SaaS",
"Software Products"
],
"domain": "Software \u0026 SaaS Products"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE/BSC - Computer Science/Engineering (or related)",
"raw": "BTech / BE / BS / MTech / MCA / ME / MS in Computer Science/Engineering, IT or related field",
"requirement": "required"
}
],
"experience": {
"max": 5,
"min": 2,
"raw": "2 - 5 years work experience"
},
"job_locations": [],
"role": "Backend Developer",
"role_aliases": [
"Software Engineer",
"Backend Engineer",
"SDE"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 6,
"heading": "Job Description",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The primary role of the",
"last_5_words": "achieve impactful outcomes."
},
"text": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to:\n\nBackend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).\nIntegrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc.)\nData engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).\nAI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.\nDistributed cloud architecture: Apply serverless and container based technologies in a micro-services environment to develop highly scalable backend codes.\nAgile development: Follow agile development processes to achieve impactful outcomes.",
"word_count": 174
},
{
"bullet_count": 7,
"heading": "Candidate Profile",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Entrepreneurial mind set with",
"last_5_words": "making teams successful."
},
"text": "Entrepreneurial mind set with a positive attitude is a must.\nPrior experience (minimum 2 years) in backend development.\nExpert knowledge of new generation technologies is a must (e.g. Machine Queues, MSA architecture, PWA architecture, No-SQL, Serverless, Redis, Python, Django, SQL, Docker/Containers/Kubernetes, etc.).\nStrong acumen in algorithmic problem solving.\nSelf-learner: highly curious, self-starter and can work with minimum supervision and guidance.\nTrack record of excellence in academics or non-academic areas, with significant accomplishments.\nExcellent written \u0026 oral communication and inter-personal skills, with high degree of comfort working in teams and making teams successful.",
"word_count": 104
}
],
"urls": [
{
"type": "other",
"url": "https://hirist.com"
}
]
},
"rejected": false,
"rejection_reason": null,
"run_id": "e5e6842a-9a1e-457e-9159-d70fb220cbf8",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 1,
"score": 1.0,
"slug": "backend-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Data Engineer",
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{
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"sentence": "Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).",
"similarity": 0.5885
},
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.",
"similarity": 0.5457
},
{
"kra_text": "Builds data ingestion pipelines to collect data from transactional databases, third-party APIs, event streams, and file sources into centralized data platforms.",
"sentence": "Integrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc. )",
"similarity": 0.462
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.5321,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "AI Engineer",
"kra_matches": [
{
"kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
"sentence": "Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).",
"similarity": 0.5704
},
{
"kra_text": "Integrates AI model API responses with application business logic, database writes, event publishing, and downstream service orchestration.",
"sentence": "AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.",
"similarity": 0.5157
},
{
"kra_text": "Integrates AI model API responses with application business logic, database writes, event publishing, and downstream service orchestration.",
"sentence": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to:",
"similarity": 0.5039
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 13,
"score": 0.53,
"slug": "ai-engineer",
"total_count": null
},
{
"display_name": "ML Engineer",
"kra_matches": [
{
"kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
"sentence": "Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).",
"similarity": 0.5614
},
{
"kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
"sentence": "AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.",
"similarity": 0.5155
},
{
"kra_text": "Builds model serving infrastructure to deploy trained models as real-time prediction APIs or batch inference jobs using TorchServe, TensorFlow Serving, or SageMaker.",
"sentence": "Backend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).",
"similarity": 0.4731
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 3,
"score": 0.5167,
"slug": "ml-engineer",
"total_count": null
},
{
"display_name": "AI Compliance Officer",
"kra_matches": [
{
"kra_text": "Reviews AI use cases and model deployments against applicable regulations, internal ethics policies, and governance guidelines prior to production approval.",
"sentence": "AI and ML modelling: Develop or work collaboratively with the Data Science team and implement AI / ML models at production scale.",
"similarity": 0.545
},
{
"kra_text": "Maps AI system behaviors and data processing activities to regulatory requirements including EU AI Act, GDPR, CCPA, and sector-specific compliance frameworks.",
"sentence": "Data engineering: Build complete understanding of data architecture, write data processing scripts to prepare data for feeding to the AI engine(s).",
"similarity": 0.5291
},
{
"kra_text": "Maps AI system behaviors and data processing activities to regulatory requirements including EU AI Act, GDPR, CCPA, and sector-specific compliance frameworks.",
"sentence": "Backend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).",
"similarity": 0.4512
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 12,
"score": 0.5084,
"slug": "ai-compliance-officer",
"total_count": null
},
{
"display_name": "React Native Developer",
"kra_matches": [
{
"kra_text": "integrate backend APIs",
"sentence": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optimization, including but not limited to:",
"similarity": 0.5393
},
{
"kra_text": "integrate backend APIs",
"sentence": "Integrations: Develop API based integrations with third party tech platforms (e.g. GDSs operating in Travel or Hospitality industries, Seller services in marketplaces like Amazon, FlipKart, Public Apps in Shopify, woocommerce; sales enablement platforms like SalesForce, Microsoft Dynamics, etc. )",
"similarity": 0.5077
},
{
"kra_text": "integrate backend APIs",
"sentence": "Backend development: Develop backend codes on Artificial intelligence modelling operating at huge scale (+1Billion data processing per day).",
"similarity": 0.4722
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 73,
"score": 0.5064,
"slug": "react-native-developer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": 6,
"matched_skills": [
"Django",
"Docker",
"NoSQL",
"Python",
"Redis",
"microservices"
],
"role_id": 1,
"score": 0.4,
"slug": "backend-engineer",
"total_count": 15
},
{
"display_name": "Engineering Manager",
"kra_matches": null,
"matched_count": 4,
"matched_skills": [
"Agile",
"Django",
"Python",
"SQL"
],
"role_id": 121,
"score": 0.2667,
"slug": "engineering-manager",
"total_count": 15
},
{
"display_name": "Fullstack Developer",
"kra_matches": null,
"matched_count": 3,
"matched_skills": [
"API",
"Django",
"Python"
],
"role_id": 15,
"score": 0.2,
"slug": "full-stack-engineer",
"total_count": 15
},
{
"display_name": "ML Engineer",
"kra_matches": null,
"matched_count": 3,
"matched_skills": [
"Kubernetes",
"Machine Learning",
"Python"
],
"role_id": 3,
"score": 0.2,
"slug": "ml-engineer",
"total_count": 15
},
{
"display_name": "MLOps Engineer",
"kra_matches": null,
"matched_count": 3,
"matched_skills": [
"Kubernetes",
"Machine Learning",
"Python"
],
"role_id": 16,
"score": 0.2,
"slug": "ml-ops-engineer",
"total_count": 15
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 1,
"score": 1.0,
"slug": "backend-engineer",
"total_count": null
},
"confidence": 1.0,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [],
"matched_kras": [],
"matched_skills": [],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top backend-engineer 0.40 does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 1021,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": {
"best_kra_similarity": 0.0,
"queue_id": 1075,
"r_and_r_preview": "The primary role of the backend developer will be to write the data integration and data processing scripts of high scalable and data computation heavy SaaS products for AI powered dynamic price optim",
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"status": "pending"
},
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 15391,
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"skill_name": "Serverless",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 15392,
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"skill_name": "SaaS",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 15393,
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"skill_name": "Containerization",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 67,
"existing_alias_text": "Python",
"input_term": "Python",
"matched_canonical": {
"category_id": 6,
"display_name": "Python",
"id": 5,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "python",
"sub_category_id": 96,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 82,
"existing_alias_text": "Django",
"input_term": "Django",
"matched_canonical": {
"category_id": 5,
"display_name": "Django",
"id": 9,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "FRAMEWORK",
"slug": "django",
"sub_category_id": 35,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 271,
"existing_alias_text": "SQL",
"input_term": "SQL",
"matched_canonical": {
"category_id": 6,
"display_name": "SQL",
"id": 101,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "sql",
"sub_category_id": 97,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 198,
"existing_alias_text": "Docker",
"input_term": "Docker",
"matched_canonical": {
"category_id": 13,
"display_name": "Docker",
"id": 61,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "docker",
"sub_category_id": 63,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1267,
"existing_alias_text": "Kubernetes",
"input_term": "Kubernetes",
"matched_canonical": {
"category_id": 9,
"display_name": "Kubernetes",
"id": 726,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "kubernetes",
"sub_category_id": 557,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 168,
"existing_alias_text": "Redis",
"input_term": "Redis",
"matched_canonical": {
"category_id": 3,
"display_name": "Redis",
"id": 31,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "redis",
"sub_category_id": 28,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 868,
"existing_alias_text": "Agile",
"input_term": "Agile",
"matched_canonical": {
"category_id": 8,
"display_name": "Agile",
"id": 520,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
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]
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"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "microservices",
"alias_type": "CANONICAL",
"id": 178,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 1,
"display_name": "microservices",
"id": 41,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PATTERN",
"slug": "microservices",
"sub_category_id": 1,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Microservices and Distributed Systems",
"id": 9,
"rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
"slug": "microservices-and-distributed-systems",
"source": "db"
},
"input_skill": "Microservices",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
}
],
"input_skill": "Microservices",
"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": "NoSQL",
"alias_type": "CANONICAL",
"id": 1989,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "NoSQL",
"id": 1346,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "nosql",
"sub_category_id": 1019,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL Databases",
"id": 19,
"rationale": "Models and manages data using non-relational database systems.",
"slug": "nosql-databases",
"source": "db"
},
"input_skill": "NoSQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
]
}
],
"input_skill": "NoSQL",
"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": "Artificial Intelligence",
"alias_type": "CANONICAL",
"id": 2016,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "Artificial Intelligence",
"id": 1357,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "artificial-intelligence",
"sub_category_id": 1020,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"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": "Artificial Intelligence",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Artificial Intelligence",
"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": "Machine Learning",
"alias_type": "CANONICAL",
"id": 2015,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"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"
},
"dimensions": [
{
"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"
},
"input_skill": "Machine Learning",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "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": "Machine Learning",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Machine Learning",
"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": "API",
"alias_type": "CANONICAL",
"id": 2514,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "API",
"id": 1568,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "api",
"sub_category_id": 1174,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "API Integration and Data Fetching",
"id": 127,
"rationale": "Client-side integration with backend endpoints and third-party services, including request shaping, response handling, and synchronization with UI state. This is central to frontend work because most screens depend on remote data.",
"slug": "api-integration-and-data-fetching",
"source": "db"
},
"input_skill": "API",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Angular Frontend Developer",
"id": 90,
"rationale": null,
"role_archetype": "Engineering",
"slug": "angular-frontend-developer",
"source": "db"
},
{
"display_name": "Frontend Developer",
"id": 7,
"rationale": null,
"role_archetype": null,
"slug": "frontend-engineer",
"source": "db"
},
{
"display_name": "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": "React Frontend Developer",
"id": 89,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-frontend-developer",
"source": "db"
},
{
"display_name": "Svelte Frontend Developer",
"id": 92,
"rationale": null,
"role_archetype": "Engineering",
"slug": "svelte-frontend-developer",
"source": "db"
},
{
"display_name": "Vue Frontend Developer",
"id": 91,
"rationale": null,
"role_archetype": "Engineering",
"slug": "vue-frontend-developer",
"source": "db"
},
{
"display_name": "Web Developer",
"id": 25,
"rationale": null,
"role_archetype": null,
"slug": "web-developer",
"source": "db"
}
]
}
],
"input_skill": "API",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "SaaS",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "saas",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Containerization",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "DevOps Tools",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "containerization",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"SaaS",
"Containerization"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Backend Developer",
"id": 1,
"rationale": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top backend-engineer 0.40 does not contradict",
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "Django",
"tag": "in_db"
},
{
"skill": "SQL",
"tag": "in_db"
},
{
"skill": "Docker",
"tag": "in_db"
},
{
"skill": "Kubernetes",
"tag": "in_db"
},
{
"skill": "Redis",
"tag": "in_db"
},
{
"skill": "Agile",
"tag": "in_db"
},
{
"skill": "Serverless",
"tag": "in_db"
},
{
"skill": "Microservices",
"tag": "in_db"
},
{
"skill": "NoSQL",
"tag": "in_db"
},
{
"skill": "Artificial Intelligence",
"tag": "in_db"
},
{
"skill": "Machine Learning",
"tag": "in_db"
},
{
"skill": "API",
"tag": "in_db"
},
{
"skill": "SaaS",
"tag": "new"
},
{
"skill": "Containerization",
"tag": "new"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Scripting \u0026 DSL Languages",
"id": 248,
"rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
"slug": "cloud-security-scripting-dsl-languages",
"source": "db"
},
"dimension_id": 248,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
"slug": "programming-languages",
"source": "db"
},
"dimension_id": 1,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 435,
"rationale": null,
"role_archetype": "Engineering",
"slug": "fullstack-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages \u0026 DSLs",
"id": 475,
"rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
"slug": "programming-languages-dsls",
"source": "db"
},
"dimension_id": 475,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"dimension_id": 59,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"dimension_id": 39,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for XR",
"id": 97,
"rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
"slug": "programming-languages-for-xr",
"source": "db"
},
"dimension_id": 97,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "AR/VR Engineer",
"id": 8,
"rationale": null,
"role_archetype": null,
"slug": "ar-vr-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Python Programming",
"id": 290,
"rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
"slug": "python-programming",
"source": "db"
},
"dimension_id": 290,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Frameworks \u0026 Libraries",
"id": 360,
"rationale": "Manage adoption, integration, and best practices around key software frameworks and libraries.",
"slug": "frameworks-libraries",
"source": "db"
},
"dimension_id": 360,
"input_skill": "Django",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Drupal Dev",
"id": 228,
"rationale": null,
"role_archetype": "Engineering",
"slug": "drupal-dev",
"source": "db"
},
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 9,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Application Frameworks",
"id": 2,
"rationale": "Server frameworks and runtimes used to build HTTP services, controllers, middleware, and request pipelines. These frameworks shape how backend endpoints are structured and delivered.",
"slug": "web-application-frameworks",
"source": "db"
},
"dimension_id": 2,
"input_skill": "Django",
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"matched_chosen_role": true,
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},
{
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},
{
"display_name": "React Frontend Developer",
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},
{
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},
{
"display_name": "Vue Frontend Developer",
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"role_archetype": "Engineering",
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},
{
"display_name": "Web Developer",
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"slug": "web-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1568,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 0,
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},
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"run_id": "e5e6842a-9a1e-457e-9159-d70fb220cbf8"
}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.