Pipeline run
0d5f1d73-508e-49ac-bc60-8671b1857c48
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
Fullstack Developer
CASE Aslug: full-stack-engineer · id: 15 · source: db
Exact alias hit on full-stack-engineer (1.0) — no other alias at this confidence; skill_top ml-engineer 0.14 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Experience: 4.00 + years Salary: INR 3000000-4800000 / year (based on experience) Expected Notice Period: 30 Days Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Remote Placement Type: Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Gather AI) What do you need for this opportunity? Must have skills required: Chrome Dev Tools, Jest, State management, React Js, Rest APIs, ANT, CI/CD, Azure, Node Js, Python, Tailwind CSS Gather AI is Looking for: Roles and Responsibilities : About You We’re looking for a Lead Full Stack Application Engineer, where your expertise in front-end web app development takes flight in the exciting challenge of empowering flying robots (drones) to perform real, impactful work. You’ll contribute to the heartbeat of our AI-focused company by crafting and maintaining web applications that enable customers to seamlessly process visually gathered information, transforming it into actionable tasks and breathing life into our cutting-edge ML and autonomy technology. You’ll also dive into the core interfaces utilized by both customers and internal teams to review and refine data collected by our drones, synthesizing it into actionable insights while constructing tools that assess product performance and measure its value for customers, seizing opportunities for growth and learning. You'll have the opportunity to flex your CS fundamentals, seamlessly blending front-end expertise with occasional forays into back-end or full-stack tasks to bring your visionary ideas to life. Join us at Gather and be part of the revolution shaping the future of AI-driven solutions! What You’ll Do Define and implement new features, fixes, and improvements to our web application suite. This includes interfaces that map warehouse physical environments, build flight schedules, control flight progress, and help our customers view immediate data insights and trends based on flight results. Help us define and refine our overall web systems information architecture - this includes things like sitemaps, user flows, wireframes, and information taxonomy. Help us build project timelines and stick to them. Together, with back-end developers, you define data models and APIs that support your scalable, flexible front end applications. Collaborate with a team of world-class autonomy, machine learning, and full-stack experts on new feature development. Develop and evolve our automated inventory monitoring and data gathering solutions. Continuously improve the performance, robustness, and scalability of our web applications as we grow, and the footprint and generality of our product as it expands. Own and eliminate the technical debt that comes with startup growth and learning. Build and maintain build scripts, tooling, and unit testing fundamental to building a mature, easy-to-evolve, and release CI/CD application platform. Act as a trusted advisor and mentor to other team members (we are growing!) Requirements : What You’ll Need BS in Computer Science/Engineering or equivalent technical experience. 4+ years of interest and experience developing front end applications. Comfort with the MERN ecosystem, including React.js, Node.js OR Python, Progressive Web Application frameworks (e.g. React), IndexedDB, Tailwind CSS, and Ant.d. Experience with transforming user pain points into intuitive and delightful interfaces with or without the help of UI/UX designers. Interest in designing before developing UI/UX interfaces using Miro/Figma and presenting them to customers and users to seek validation. Experience working with CI/CD testing tools and releasing production software through the cloud ecosystems. Extensive experience defining data models and APIs with back-end developers that can support scalable, flexible frontend applications. Knowledge of and comfort with JS threading, callback, and unit testing best practices. Good writing skills and a design-for-test ethos. Customer obsession! We are a customer-obsessed company. If you are not already customer-obsessed, expect to become so! Nice to Have Some prior startup growth experience. We are a small but fast-growing company, and we are looking for candidates who are ready to grow their skills with us. Interest and proficiency in developing rich, possibly event-driven APIs involving multiple concurrent users (and drones!) GraphQL and gRPC experience - we have rich views on data and are considering these technologies. Compensation And Benefits Salary: 30-50 LPA Flexible schedule Unlimited paid leave Remote work & home office stipend Wellness benefits If this sounds like a good fit we’d love to meet you. Robotics is the future and we’re leading the charge with our software-only business model. Come help us change the world! How to apply for this opportunity? • Register or login on our portal & fill out the application form. • Clear the given Video Screening (30 min) and Click on 'Apply' to get shortlisted • Once it's all done, your profile will be shared with the client for the Interview round. • When selected, just meet the client and get your exciting career started! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. You will also be assigned to a dedicated Talent Success Coach during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Web Frameworks
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- APIs (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Protocol
- Sub-category
- Application Programming Interfaces
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: APIs are a hiring-pipeline staple across backend, mobile, and platform JDs; REST/GraphQL/API design appears in large volumes of job postings and vendor docs, indicating broad adoption.
Skill profile (library / DB)
- Skill nature
- PROTOCOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 10
- Sub-category id
- 902
- 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
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- 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
- CI/CD (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Ci Cd Process
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: CI/CD appears in a large share of software engineering JDs and is a standard requirement across DevOps, platform, and backend roles; major vendors like GitHub, GitLab, and AWS all center product roadmaps on CI/CD pipelines.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 900
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
CI/CD Pipeline Platforms Catalog dimension db id 150
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
CI/CD for Machine Learning Catalog dimension db id 56
Library dimension (catalog)
Roles linked in library: ML Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Unit Testing (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Testing Methodology
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Unit testing is a standard hiring requirement across software JDs and appears in mainstream frameworks/docs; GitHub and Stack Overflow usage remain consistently high, with no successor replacing it.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 44
- 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
- Infrastructure 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
- Infrastructure 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 |
|---|---|---|---|---|---|---|
| APIs | 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) | |
| CI/CD | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CI/CD | in_db |
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Unit Testing | 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 | Web Application Development | type=Web Frameworks subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Models | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Build Scripts | type=Infrastructure Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Automation | type=Infrastructure Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "About Uplers: Our goal is",
"last_5_words": "during the engagement."
},
"text": "About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. You will also be assigned to a dedicated Talent Success Coach during the engagement.",
"word_count": 64
},
"certifications": [],
"company_name": "Gather AI",
"ctc": {
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"max": 4800000,
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},
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},
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},
"education": [
{
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"qualification": "BTECH/BE - Computer Science/Engineering (or equivalent)",
"raw": "BS in Computer Science/Engineering or equivalent technical experience.",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 4,
"raw": "4+ years of interest and experience developing front end applications."
},
"job_locations": [
{
"aliases": [],
"city": null,
"country": "India",
"state": null,
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}
],
"role": "Lead Full Stack Application Engineer",
"role_aliases": [
"Full Stack Engineer",
"Lead Engineer",
"Full Stack Developer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Roles and Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Define and implement new features,",
"last_5_words": "to other team members (we are growing!)"
},
"text": "Define and implement new features, fixes, and improvements to our web application suite. This includes interfaces that map warehouse physical environments, build flight schedules, control flight progress, and help our customers view immediate data insights and trends based on flight results.\nHelp us define and refine our overall web systems information architecture - this includes things like sitemaps, user flows, wireframes, and information taxonomy.\nHelp us build project timelines and stick to them.\nTogether, with back-end developers, you define data models and APIs that support your scalable, flexible front end applications.\nCollaborate with a team of world-class autonomy, machine learning, and full-stack experts on new feature development. Develop and evolve our automated inventory monitoring and data gathering solutions.\nContinuously improve the performance, robustness, and scalability of our web applications as we grow, and the footprint and generality of our product as it expands.\nOwn and eliminate the technical debt that comes with startup growth and learning.\nBuild and maintain build scripts, tooling, and unit testing fundamental to building a mature, easy-to-evolve, and release CI/CD application platform.\nAct as a trusted advisor and mentor to other team members (we are growing!)",
"word_count": 218
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Web Application Development"
},
{
"is_primary": true,
"skill_name": "APIs"
},
{
"is_primary": true,
"skill_name": "Data Models"
},
{
"is_primary": false,
"skill_name": "Machine Learning"
},
{
"is_primary": true,
"skill_name": "CI/CD"
},
{
"is_primary": true,
"skill_name": "Unit Testing"
},
{
"is_primary": true,
"skill_name": "Build Scripts"
},
{
"is_primary": true,
"skill_name": "Automation"
}
],
"jd_role": {
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"role_aliases": [
"Full Stack Engineer",
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"nano_parsed": {
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"run_id": "0d5f1d73-508e-49ac-bc60-8671b1857c48",
"stage3_signals": {
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"alias_match_roles": [
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"kra_match_roles": [
{
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{
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],
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{
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{
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{
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{
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],
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{
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{
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{
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{
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},
{
"display_name": "Frontend Developer",
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{
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"similarity": 0.5591
},
{
"kra_text": "Optimizes web application performance through code splitting, lazy loading, tree shaking, bundle size reduction, and Core Web Vitals improvements.",
"sentence": "Continuously improve the performance, robustness, and scalability of our web applications as we grow, and the footprint and generality of our product as it expands.",
"similarity": 0.5191
},
{
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}
],
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},
{
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{
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"sentence": "Together, with back-end developers, you define data models and APIs that support your scalable, flexible front end applications.",
"similarity": 0.537
},
{
"kra_text": "Configures Docker containers, deployment descriptors, environment variables, and CI/CD pipeline stages for backend service releases.",
"sentence": "Build and maintain build scripts, tooling, and unit testing fundamental to building a mature, easy-to-evolve, and release CI/CD application platform.",
"similarity": 0.5273
},
{
"kra_text": "Investigates and resolves production incidents, API bugs, and service degradation through root cause analysis, hotfixes, and post-mortems.",
"sentence": "Define and implement new features, fixes, and improvements to our web application suite.",
"similarity": 0.433
}
],
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}
],
"skill_match_roles": [
{
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"matched_skills": [
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},
{
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},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
"display_name": "Fullstack Developer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 1.0,
"slug": "full-stack-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 full-stack-engineer (1.0) \u2014 no other alias at this confidence; skill_top ml-engineer 0.14 does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 212,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 8998,
"role_display_name": "Fullstack Developer",
"role_slug": "full-stack-engineer",
"skill_name": "Web Application Development",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 8999,
"role_display_name": "Fullstack Developer",
"role_slug": "full-stack-engineer",
"skill_name": "Data Models",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 9000,
"role_display_name": "Fullstack Developer",
"role_slug": "full-stack-engineer",
"skill_name": "Build Scripts",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 9001,
"role_display_name": "Fullstack Developer",
"role_slug": "full-stack-engineer",
"skill_name": "Automation",
"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": 1828,
"existing_alias_text": "APIs",
"input_term": "APIs",
"matched_canonical": {
"category_id": 10,
"display_name": "APIs",
"id": 1192,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PROTOCOL",
"slug": "apis",
"sub_category_id": 902,
"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": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1826,
"existing_alias_text": "CI/CD",
"input_term": "CI/CD",
"matched_canonical": {
"category_id": 8,
"display_name": "CI/CD",
"id": 1190,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "ci-cd",
"sub_category_id": 900,
"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": 865,
"existing_alias_text": "Unit Testing",
"input_term": "Unit Testing",
"matched_canonical": {
"category_id": 8,
"display_name": "Unit Testing",
"id": 517,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "unit-testing",
"sub_category_id": 44,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
"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"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
],
"chosen_role": {
"display_name": "Fullstack Developer",
"id": 15,
"rationale": "Exact alias hit on full-stack-engineer (1.0) \u2014 no other alias at this confidence; skill_top ml-engineer 0.14 does not contradict",
"role_archetype": null,
"slug": "full-stack-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": "APIs",
"llm_role": null,
"roles_from_db": []
},
{
"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": []
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD Pipeline Platforms",
"id": 150,
"rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
"slug": "ci-cd-pipeline-platforms",
"source": "db"
},
"input_skill": "CI/CD",
"llm_role": null,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD for Machine Learning",
"id": 56,
"rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
"slug": "ci-cd-for-machine-learning",
"source": "db"
},
"input_skill": "CI/CD",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "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": "Unit Testing",
"llm_role": null,
"roles_from_db": []
}
],
"input_final_skills": [
"Web Application Development",
"APIs",
"Data Models",
"Machine Learning",
"CI/CD",
"Unit Testing",
"Build Scripts",
"Automation"
],
"input_llm_skills": [
"Web Application Development",
"APIs",
"Data Models",
"Machine Learning",
"CI/CD",
"Unit Testing",
"Build Scripts",
"Automation"
],
"new_aliases_persisted": 0,
"run_id": "0d5f1d73-508e-49ac-bc60-8671b1857c48",
"skills_detail": [
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Web Application Development",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Web Frameworks",
"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": "web-application-development",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "APIs",
"alias_type": "CANONICAL",
"id": 1828,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 10,
"display_name": "APIs",
"id": 1192,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PROTOCOL",
"slug": "apis",
"sub_category_id": 902,
"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": "APIs",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "APIs",
"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 Models",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "EVERGREEN",
"version_strategy": "UNVERSIONED",
"volatility": "STABLE"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "data-models",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"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": "CI/CD",
"alias_type": "CANONICAL",
"id": 1826,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "CI/CD",
"id": 1190,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "ci-cd",
"sub_category_id": 900,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD Pipeline Platforms",
"id": 150,
"rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
"slug": "ci-cd-pipeline-platforms",
"source": "db"
},
"input_skill": "CI/CD",
"llm_role": null,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD for Machine Learning",
"id": 56,
"rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
"slug": "ci-cd-for-machine-learning",
"source": "db"
},
"input_skill": "CI/CD",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
}
]
}
],
"input_skill": "CI/CD",
"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": "Unit Testing",
"alias_type": "CANONICAL",
"id": 865,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "Unit Testing",
"id": 517,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "unit-testing",
"sub_category_id": 44,
"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": "Unit Testing",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Unit Testing",
"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": "Build Scripts",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Infrastructure 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": "build-scripts",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Automation",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Infrastructure 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": "automation",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Web Application Development",
"Data Models",
"Build Scripts",
"Automation"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Fullstack Developer",
"id": 15,
"rationale": "Exact alias hit on full-stack-engineer (1.0) \u2014 no other alias at this confidence; skill_top ml-engineer 0.14 does not contradict",
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Web Application Development",
"tag": "new"
},
{
"skill": "APIs",
"tag": "in_db"
},
{
"skill": "Data Models",
"tag": "new"
},
{
"skill": "Machine Learning",
"tag": "in_db"
},
{
"skill": "CI/CD",
"tag": "in_db"
},
{
"skill": "Unit Testing",
"tag": "in_db"
},
{
"skill": "Build Scripts",
"tag": "new"
},
{
"skill": "Automation",
"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": 15,
"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": "APIs",
"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": 1192,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 15,
"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": 15,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
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}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.