Pipeline run
f599fb04-fb33-40c9-b5cd-b3252db14074
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded
sources · ai_index: jd · nature_of_work: no_kras · tech_stack_maturity: jd
Nature of work
no kras
Vague JD — no KRAs present to derive a specific nature of work.
Tech stack maturity
Mainstream Modern
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.00 / 5
· Title match
· Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
—
Frameworks (×2):
—
Models / concepts (×3):
—
Evidence — skills matched in JD (0)
Skill cluster (0 dimension groups, role-scoped)
Status:
completed
Created: 2026-05-08T17:11:05.083807Z
Updated: 2026-05-08T17:12:37.280729Z
API 3 duration: 27 ms
Flow
Current 3-step pipeline
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Role
Chosen role & resolution
DevOps Engineer
slug: devops-engineer · id: 1 · source: db
Most dimensions map to DevOps/Cloud roles, with the strongest coverage around Kubernetes, cloud platforms, Docker, and CI/CD.
0
New skills
0
Skill↔dim saved
0
Role↔dim saved
21
Skipped
Job description
Job Description: We are looking for a skilled java developer with 6+ plus years of experience to contribute to the development of robust, efficient, and scalable server-side solutions. The ideal candidate will play a pivotal role in shaping our back-end architecture, collaborating with our front-end developers, and ensuring the performance and reliability of our applications. Key Responsibilities: Design, develop, and maintain server-side logic for high-performance web applications. Collaborate with front-end developers to integrate user-facing elements with server-side logic. Optimize applications for maximum speed and scalability. Implement data security and protection measures. Troubleshoot and debug issues that arise during development and testing. Build reusable code and libraries for future use. Stay up to date with the latest industry trends, best practices, and emerging technologies. Work closely with cross-functional teams to understand and address business needs. Qualifications: Bachelor’s degree in computer science, Software Engineering, or a related field (or equivalent work experience). 6 plus years of experience in back-end web development Proficiency in one or more server-side programming languages Experience with databases and data modelling (SQL and/or NoSQL databases) Familiarity with RESTful API design and development Strong understanding of server-side architecture and microservices. Knowledge of version control systems (e.g., Git) Strong problem-solving skills and attention to detail Strong communication and collaboration skills. Ability to work independently and as part of a team. Nice-to-Have Skills: Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes) Security best practices in web application development Performance optimization and scalability techniques Familiarity with message queuing systems (e.g., RabbitMQ, Kafka) Experience with DevOps practices and CI/CD pipelines
history_view bundle (older API). Showing raw API payloads below.
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 |
|---|---|---|---|---|---|---|
| Kubernetes | in_db |
Orchestration Platforms
orchestration-platforms
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Google Cloud | in_db |
Cloud Platform Operations
cloud-platform-operations
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Docker | in_db |
Containerization and Image Delivery
containerization-and-image-delivery
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Docker | in_db |
Model Serving Deployment and Runtime Packaging
model-serving-deployment-and-runtime-packaging
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| REST API | in_db |
Platform Integrations and APIs
platform-integrations-and-apis
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| RabbitMQ | in_db |
Messaging and Event Streaming
messaging-and-event-streaming
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Java | in_db |
Programming Languages for AI Workflows
programming-languages-for-ai-workflows
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Java | in_db |
Programming Languages for Backend Systems
programming-languages-for-backend-systems
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Java | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Java | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Java | in_db |
Programming Languages for Test Automation
programming-languages-for-test-automation
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Azure | in_db |
Cloud Platform Operations
cloud-platform-operations
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Kafka | in_db |
Messaging and Event Streaming
messaging-and-event-streaming
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| Microservices | in_db |
Service Architecture and Integration
service-architecture-and-integration
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| AWS | in_db |
Cloud Platform Operations
cloud-platform-operations
|
— | — | — | TODO: REMOVE AFTER TESTING — api3_writes_enabled=False (writes disabled) |
| API | new |
API Design and Integration
d_init_01
|
— | — | — | skill_not_in_db_v3_proposed |
| CD | new |
Continuous Delivery
d_init_01
|
— | — | — | skill_not_in_db_v3_proposed |
| CI | new |
Continuous Integration
d_init_01
|
— | — | — | skill_not_in_db_v3_proposed |
| Cloud | new |
Cloud Platforms and Services
d_init_01
|
— | — | — | skill_not_in_db_v3_proposed |
| SQL | new |
SQL Querying and Relational Data
d_init_01
|
— | — | — | skill_not_in_db_v3_proposed |
| Security | new |
Security
d_init_01
|
— | — | — | skill_not_in_db_v3_proposed |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | API | type=Protocol subtype=application_programming_interface nature=PROTOCOL lifespan=EVERGREEN | |
| canonical_skill_proposed | CD | type=Methodology subtype=continuous_delivery nature=METHODOLOGY lifespan=EVERGREEN | |
| canonical_skill_proposed | CI | type=Methodology subtype=continuous_integration_methodology nature=METHODOLOGY lifespan=EVERGREEN | |
| canonical_skill_proposed | Cloud | type=Platform subtype=cloud_computing_platform nature=PLATFORM lifespan=EVERGREEN | |
| canonical_skill_proposed | SQL | type=Language subtype=query_language nature=LANGUAGE lifespan=EVERGREEN | |
| canonical_skill_proposed | Security | type=Domain subtype=security nature=CONCEPT lifespan=EVERGREEN | |
| dimension_proposed | API Design and Integration | |
| dimension_skill_link_proposed | API ↔ API Design and Integration | |
| dimension_proposed | Continuous Delivery | |
| dimension_skill_link_proposed | CD ↔ Continuous Delivery | |
| dimension_proposed | Continuous Integration | |
| dimension_skill_link_proposed | CI ↔ Continuous Integration | |
| dimension_proposed | Cloud Platforms and Services | |
| dimension_skill_link_proposed | Cloud ↔ Cloud Platforms and Services | |
| dimension_proposed | SQL Querying and Relational Data | |
| dimension_skill_link_proposed | SQL ↔ SQL Querying and Relational Data | |
| dimension_proposed | Security | |
| dimension_skill_link_proposed | Security ↔ Security |
API 1 — extract-from-jd click to toggle
{
"filtered_unknown_words": [
"API",
"Ability",
"Bachelor",
"CD",
"CI",
"Cloud",
"Description",
"Design",
"Engineering",
"Experience",
"Familiarity",
"Google",
"Job",
"Key",
"Knowledge",
"Optimize",
"Performance",
"Proficiency",
"Qualifications",
"Responsibilities",
"SQL",
"Security",
"Skills",
"Software",
"application",
"applications",
"architecture",
"attention",
"business",
"candidate",
"cloud",
"code",
"collaboration",
"communication",
"computer",
"control",
"data",
"databases",
"date",
"degree",
"design",
"detail",
"developer",
"developers",
"development",
"elements",
"end",
"experience",
"field",
"industry",
"issues",
"languages",
"libraries",
"logic",
"measures",
"message",
"modelling",
"needs",
"optimization",
"orchestration",
"performance",
"pipelines",
"platforms",
"practices",
"problem",
"programming",
"protection",
"queuing",
"role",
"science",
"security",
"server",
"skills",
"solutions",
"speed",
"systems",
"team",
"teams",
"techniques",
"technologies",
"testing",
"trends",
"understanding",
"use",
"user",
"version",
"web",
"work",
"years"
],
"final_non_skills": [
"Ability",
"Bachelor",
"Description",
"Design",
"Engineering",
"Experience",
"Familiarity",
"Google",
"Job",
"Key",
"Knowledge",
"Optimize",
"Performance",
"Proficiency",
"Qualifications",
"Responsibilities",
"Skills",
"Software",
"applications",
"attention",
"business",
"candidate",
"collaboration",
"communication",
"computer",
"control",
"data",
"date",
"degree",
"detail",
"developer",
"developers",
"elements",
"end",
"field",
"industry",
"issues",
"languages",
"libraries",
"logic",
"measures",
"needs",
"optimization",
"practices",
"problem",
"protection",
"role",
"science",
"speed",
"team",
"teams",
"techniques",
"trends",
"understanding",
"use",
"user",
"version",
"work",
"years"
],
"final_skills": [
"Kubernetes",
"Google Cloud",
"Docker",
"REST API",
"RabbitMQ",
"Java",
"Azure",
"Kafka",
"Microservices",
"AWS",
"API",
"CD",
"CI",
"Cloud",
"SQL",
"Security",
"application",
"architecture",
"code",
"databases",
"development",
"message",
"orchestration",
"pipelines",
"platforms",
"programming",
"queuing",
"server",
"solutions",
"systems",
"technologies",
"testing",
"web"
],
"initial_skills": [
"Kubernetes",
"Google Cloud",
"Docker",
"REST API",
"RabbitMQ",
"Java",
"Azure",
"Kafka",
"Microservices",
"AWS"
],
"jd_role_hint": {
"display_name": "Java Backend Developer",
"rationale": "The excerpt centers on Java, server-side development, web applications, architecture, and collaboration with front-end developers.",
"role_archetype": "Builds and maintains server-side application logic and APIs, often in a cloud and microservices environment.",
"slug": "java-backend-developer"
},
"llm_non_skills": [
"Ability",
"Bachelor",
"Description",
"Design",
"Engineering",
"Experience",
"Familiarity",
"Google",
"Job",
"Key",
"Knowledge",
"Optimize",
"Performance",
"Proficiency",
"Qualifications",
"Responsibilities",
"Skills",
"Software",
"applications",
"attention",
"business",
"candidate",
"collaboration",
"communication",
"computer",
"control",
"data",
"date",
"degree",
"detail",
"developer",
"developers",
"elements",
"end",
"field",
"industry",
"issues",
"languages",
"libraries",
"logic",
"measures",
"needs",
"optimization",
"practices",
"problem",
"protection",
"role",
"science",
"speed",
"team",
"teams",
"techniques",
"trends",
"understanding",
"use",
"user",
"version",
"work",
"years"
],
"llm_skills": [
"API",
"CD",
"CI",
"Cloud",
"SQL",
"Security",
"application",
"architecture",
"cloud",
"code",
"databases",
"development",
"message",
"orchestration",
"pipelines",
"platforms",
"programming",
"queuing",
"security",
"server",
"solutions",
"systems",
"technologies",
"testing",
"web"
],
"run_id": null,
"unknown_words": [
"API",
"Ability",
"Bachelor",
"CD",
"CI",
"Cloud",
"Description",
"Design",
"Engineering",
"Experience",
"Familiarity",
"Google",
"Job",
"Key",
"Knowledge",
"Optimize",
"Performance",
"Proficiency",
"Qualifications",
"Responsibilities",
"SQL",
"Security",
"Skills",
"Software",
"application",
"applications",
"architecture",
"attention",
"business",
"candidate",
"cloud",
"code",
"collaboration",
"communication",
"computer",
"control",
"data",
"databases",
"date",
"degree",
"design",
"detail",
"developer",
"developers",
"development",
"elements",
"end",
"experience",
"field",
"industry",
"issues",
"languages",
"libraries",
"logic",
"measures",
"message",
"modelling",
"needs",
"optimization",
"orchestration",
"performance",
"pipelines",
"platforms",
"practices",
"problem",
"programming",
"protection",
"queuing",
"role",
"science",
"security",
"server",
"skills",
"solutions",
"speed",
"systems",
"team",
"teams",
"techniques",
"technologies",
"testing",
"trends",
"understanding",
"use",
"user",
"version",
"web",
"work",
"years"
]
}
API 2 — extract-details
{
"alias_matches": [],
"candidate_roles": [
{
"display_name": "Cloud Engineer",
"id": 18,
"rationale": null,
"role_archetype": null,
"slug": "cloud-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "mlops-engineer",
"source": "db"
},
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
},
{
"display_name": "ServiceNOW Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "servicenow-developer",
"source": "db"
},
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "AI Engineer",
"id": 12,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "Automation Tester",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "automation-tester",
"source": "db"
}
],
"chosen_role": {
"display_name": "DevOps Engineer",
"id": 1,
"rationale": "Most dimensions map to DevOps/Cloud roles, with the strongest coverage around Kubernetes, cloud platforms, Docker, and CI/CD.",
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Orchestration Platforms",
"id": 25,
"rationale": "Operates the platforms that schedule and run containerized workloads and related deployment primitives. This is separate from image delivery because it concerns runtime placement and service rollout behavior.",
"slug": "orchestration-platforms",
"source": "db"
},
"input_skill": "Kubernetes",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Engineer",
"id": 18,
"rationale": null,
"role_archetype": null,
"slug": "cloud-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platform Operations",
"id": 26,
"rationale": "Uses cloud provider services to support delivery and runtime environments. The focus is on consumer-level operation of cloud services rather than deep cloud architecture ownership.",
"slug": "cloud-platform-operations",
"source": "db"
},
"input_skill": "Google Cloud",
"llm_role": null,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Containerization and Image Delivery",
"id": 24,
"rationale": "Builds, packages, and ships application and support workloads as container images. This cluster covers the artifact format and the mechanics of producing deployable images.",
"slug": "containerization-and-image-delivery",
"source": "db"
},
"input_skill": "Docker",
"llm_role": null,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Model Serving Deployment and Runtime Packaging",
"id": 52,
"rationale": "Operational deployment of trained models into online, batch, or streaming serving environments, including packaging models and model servers into containers or managed inference runtimes, coordinating rollout, and handing off to inference systems. Covers serving frameworks and platforms such as TensorFlow Serving, TorchServe, Triton Inference Server, BentoML, KServe, and Seldon Core, plus container/runtime concerns like Docker images, GPU-enabled containers, base image selection, container entrypoints, runtime dependencies, and image scanning for model services.",
"slug": "model-serving-deployment-and-runtime-packaging",
"source": "db"
},
"input_skill": "Docker",
"llm_role": null,
"roles_from_db": [
{
"display_name": "MLOps Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "mlops-engineer",
"source": "db"
},
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Platform Integrations and APIs",
"id": 215,
"rationale": "Connecting ServiceNow to external systems through APIs, web services, and integration patterns. This is a coherent cluster because developers frequently build inbound and outbound data exchange for workflow automation.",
"slug": "platform-integrations-and-apis",
"source": "db"
},
"input_skill": "REST API",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ServiceNOW Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "servicenow-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Messaging and Event Streaming",
"id": 146,
"rationale": "Asynchronous communication patterns and systems for decoupled service interaction and background processing. This is a coherent backend cluster because many server-side workflows depend on queues, topics, and event streams.",
"slug": "messaging-and-event-streaming",
"source": "db"
},
"input_skill": "RabbitMQ",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for AI Workflows",
"id": 261,
"rationale": "Languages used to implement AI feature logic, orchestration, and response handling inside product code. This is the core coding surface for turning prompts and model calls into reliable application behavior.",
"slug": "programming-languages-for-ai-workflows",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 12,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Backend Systems",
"id": 140,
"rationale": "Languages used to implement server-side business logic, request handlers, workers, and service integrations. This is the core coding surface for backend feature delivery and maintenance.",
"slug": "programming-languages-for-backend-systems",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 67,
"rationale": "Languages used to implement data pipelines, transformations, and operational utilities. This is the code layer for expressing extraction, parsing, validation, and orchestration logic in data engineering workflows.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 113,
"rationale": "Languages used to implement model integration code, inference services, and feature-processing logic. This is the core coding surface for turning trained models into product-facing software components.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
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"canonical": null,
"dimensions": [],
"input_skill": "testing",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "web",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"API",
"CD",
"CI",
"Cloud",
"SQL",
"Security"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "DevOps Engineer",
"id": 1,
"rationale": "Most dimensions map to DevOps/Cloud roles, with the strongest coverage around Kubernetes, cloud platforms, Docker, and CI/CD.",
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
},
"final_input_skills": [
{
"skill": "Kubernetes",
"tag": "in_db"
},
{
"skill": "Google Cloud",
"tag": "in_db"
},
{
"skill": "Docker",
"tag": "in_db"
},
{
"skill": "REST API",
"tag": "in_db"
},
{
"skill": "RabbitMQ",
"tag": "in_db"
},
{
"skill": "Java",
"tag": "in_db"
},
{
"skill": "Azure",
"tag": "in_db"
},
{
"skill": "Kafka",
"tag": "in_db"
},
{
"skill": "Microservices",
"tag": "in_db"
},
{
"skill": "AWS",
"tag": "in_db"
},
{
"skill": "API",
"tag": "new"
},
{
"skill": "CD",
"tag": "new"
},
{
"skill": "CI",
"tag": "new"
},
{
"skill": "Cloud",
"tag": "new"
},
{
"skill": "SQL",
"tag": "new"
},
{
"skill": "Security",
"tag": "new"
},
{
"skill": "application",
"tag": "new"
},
{
"skill": "architecture",
"tag": "new"
},
{
"skill": "code",
"tag": "new"
},
{
"skill": "databases",
"tag": "new"
},
{
"skill": "development",
"tag": "new"
},
{
"skill": "message",
"tag": "new"
},
{
"skill": "orchestration",
"tag": "new"
},
{
"skill": "pipelines",
"tag": "new"
},
{
"skill": "platforms",
"tag": "new"
},
{
"skill": "programming",
"tag": "new"
},
{
"skill": "queuing",
"tag": "new"
},
{
"skill": "server",
"tag": "new"
},
{
"skill": "solutions",
"tag": "new"
},
{
"skill": "systems",
"tag": "new"
},
{
"skill": "technologies",
"tag": "new"
},
{
"skill": "testing",
"tag": "new"
},
{
"skill": "web",
"tag": "new"
}
],
"persistence": {
"items": [
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Orchestration Platforms",
"id": 25,
"rationale": "Operates the platforms that schedule and run containerized workloads and related deployment primitives. This is separate from image delivery because it concerns runtime placement and service rollout behavior.",
"slug": "orchestration-platforms",
"source": "db"
},
"dimension_id": 25,
"input_skill": "Kubernetes",
"llm_role": null,
"matched_chosen_role": true,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Engineer",
"id": 18,
"rationale": null,
"role_archetype": null,
"slug": "cloud-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 158,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platform Operations",
"id": 26,
"rationale": "Uses cloud provider services to support delivery and runtime environments. The focus is on consumer-level operation of cloud services rather than deep cloud architecture ownership.",
"slug": "cloud-platform-operations",
"source": "db"
},
"dimension_id": 26,
"input_skill": "Google Cloud",
"llm_role": null,
"matched_chosen_role": true,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 165,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Containerization and Image Delivery",
"id": 24,
"rationale": "Builds, packages, and ships application and support workloads as container images. This cluster covers the artifact format and the mechanics of producing deployable images.",
"slug": "containerization-and-image-delivery",
"source": "db"
},
"dimension_id": 24,
"input_skill": "Docker",
"llm_role": null,
"matched_chosen_role": true,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 153,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Model Serving Deployment and Runtime Packaging",
"id": 52,
"rationale": "Operational deployment of trained models into online, batch, or streaming serving environments, including packaging models and model servers into containers or managed inference runtimes, coordinating rollout, and handing off to inference systems. Covers serving frameworks and platforms such as TensorFlow Serving, TorchServe, Triton Inference Server, BentoML, KServe, and Seldon Core, plus container/runtime concerns like Docker images, GPU-enabled containers, base image selection, container entrypoints, runtime dependencies, and image scanning for model services.",
"slug": "model-serving-deployment-and-runtime-packaging",
"source": "db"
},
"dimension_id": 52,
"input_skill": "Docker",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "MLOps Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "mlops-engineer",
"source": "db"
},
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 153,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Platform Integrations and APIs",
"id": 215,
"rationale": "Connecting ServiceNow to external systems through APIs, web services, and integration patterns. This is a coherent cluster because developers frequently build inbound and outbound data exchange for workflow automation.",
"slug": "platform-integrations-and-apis",
"source": "db"
},
"dimension_id": 215,
"input_skill": "REST API",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "ServiceNOW Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "servicenow-developer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 1294,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Messaging and Event Streaming",
"id": 146,
"rationale": "Asynchronous communication patterns and systems for decoupled service interaction and background processing. This is a coherent backend cluster because many server-side workflows depend on queues, topics, and event streams.",
"slug": "messaging-and-event-streaming",
"source": "db"
},
"dimension_id": 146,
"input_skill": "RabbitMQ",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 853,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for AI Workflows",
"id": 261,
"rationale": "Languages used to implement AI feature logic, orchestration, and response handling inside product code. This is the core coding surface for turning prompts and model calls into reliable application behavior.",
"slug": "programming-languages-for-ai-workflows",
"source": "db"
},
"dimension_id": 261,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 12,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Backend Systems",
"id": 140,
"rationale": "Languages used to implement server-side business logic, request handlers, workers, and service integrations. This is the core coding surface for backend feature delivery and maintenance.",
"slug": "programming-languages-for-backend-systems",
"source": "db"
},
"dimension_id": 140,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 67,
"rationale": "Languages used to implement data pipelines, transformations, and operational utilities. This is the code layer for expressing extraction, parsing, validation, and orchestration logic in data engineering workflows.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 67,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 113,
"rationale": "Languages used to implement model integration code, inference services, and feature-processing logic. This is the core coding surface for turning trained models into product-facing software components.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"dimension_id": 113,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Machine Learning Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "machine-learning-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Test Automation",
"id": 193,
"rationale": "Languages used to implement automated checks, helper utilities, and test harness code. This is the core coding surface for turning test ideas into maintainable automation.",
"slug": "programming-languages-for-test-automation",
"source": "db"
},
"dimension_id": 193,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Automation Tester",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "automation-tester",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 395,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platform Operations",
"id": 26,
"rationale": "Uses cloud provider services to support delivery and runtime environments. The focus is on consumer-level operation of cloud services rather than deep cloud architecture ownership.",
"slug": "cloud-platform-operations",
"source": "db"
},
"dimension_id": 26,
"input_skill": "Azure",
"llm_role": null,
"matched_chosen_role": true,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 164,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Messaging and Event Streaming",
"id": 146,
"rationale": "Asynchronous communication patterns and systems for decoupled service interaction and background processing. This is a coherent backend cluster because many server-side workflows depend on queues, topics, and event streams.",
"slug": "messaging-and-event-streaming",
"source": "db"
},
"dimension_id": 146,
"input_skill": "Kafka",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 852,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Service Architecture and Integration",
"id": 148,
"rationale": "Patterns for structuring backend systems as services and coordinating calls across internal and external dependencies. This includes how services are decomposed, connected, and evolved safely.",
"slug": "service-architecture-and-integration",
"source": "db"
},
"dimension_id": 148,
"input_skill": "Microservices",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Engineer",
"id": 14,
"rationale": null,
"role_archetype": null,
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 864,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platform Operations",
"id": 26,
"rationale": "Uses cloud provider services to support delivery and runtime environments. The focus is on consumer-level operation of cloud services rather than deep cloud architecture ownership.",
"slug": "cloud-platform-operations",
"source": "db"
},
"dimension_id": 26,
"input_skill": "AWS",
"llm_role": null,
"matched_chosen_role": true,
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 1,
"rationale": null,
"role_archetype": "A DevOps Engineer enables reliable, repeatable delivery of software by designing and operating the processes that connect development and production. They focus on improving deployment flow, operational stability, and collaboration between teams through automation, standardization, and monitoring of delivery and runtime practices.",
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": 163,
"skill_tag": "in_db",
"skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 api3_writes_enabled=False (writes disabled)"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": null,
"display_name": "API Design and Integration",
"id": null,
"rationale": "Designing and using application programming interfaces for backend communication, including endpoint structure, request/response contracts, and integration patterns. The skill API belongs here because it is the core abstraction for exposing and consuming backend capabilities.",
"slug": "d_init_01",
"source": "llm"
},
"dimension_id": null,
"input_skill": "API",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": null,
"display_name": "Continuous Delivery",
"id": null,
"rationale": "Practices for automatically building, testing, and promoting software changes toward production with low manual friction. CD fits here because it commonly refers to the delivery pipeline and release automation layer in backend engineering.",
"slug": "d_init_01",
"source": "llm"
},
"dimension_id": null,
"input_skill": "CD",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": null,
"display_name": "Continuous Integration",
"id": null,
"rationale": "Practices and tooling for automatically building and validating code changes whenever they are committed or merged. CI belongs here because it is the core automation loop that compiles code, runs checks, and surfaces integration problems early.",
"slug": "d_init_01",
"source": "llm"
},
"dimension_id": null,
"input_skill": "CI",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": null,
"display_name": "Cloud Platforms and Services",
"id": null,
"rationale": "Covers the core concepts, services, and operational building blocks of public cloud environments such as AWS, Azure, and GCP. The skill \"Cloud\" is broad and usually refers to working with cloud-hosted infrastructure, managed services, and deployment/runtime choices rather than a narrower subtopic like security or provisioning.",
"slug": "d_init_01",
"source": "llm"
},
"dimension_id": null,
"input_skill": "Cloud",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": null,
"display_name": "SQL Querying and Relational Data",
"id": null,
"rationale": "Covers writing, reading, and reasoning about SQL for relational databases. SQL belongs here because it is the core language for querying tables, joining data, filtering results, and expressing aggregations in backend and data systems.",
"slug": "d_init_01",
"source": "llm"
},
"dimension_id": null,
"input_skill": "SQL",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 1,
"dimension": {
"difficulty_hint": null,
"display_name": "Security",
"id": null,
"rationale": "General security knowledge for Java backend development, including protecting services, data, and access paths. This fits when the skill is broad and not clearly limited to cloud, frontend, or vulnerability remediation.",
"slug": "d_init_01",
"source": "llm"
},
"dimension_id": null,
"input_skill": "Security",
"llm_role": null,
"matched_chosen_role": false,
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
}
],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 21
},
"planner_output": null,
"run_id": "f599fb04-fb33-40c9-b5cd-b3252db14074"
}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.
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