Pipeline run
d9185637-bb55-4d40-a917-b39989c3b685
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
AI Engineer
CASE Aslug: ai-engineer · id: 13 · source: db
Multi-alias tie (3 roles at 1.0) resolved by TIER_B_TITLE: AI Engineer
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
About Eagle Eye Networks Eagle Eye Networks is the global leader in cloud video surveillance, delivering AI-powered video intelligence to tens of thousands of businesses across 90+ countries. Headquartered in Austin, Texas, with development teams in Austin, Bangalore, Amsterdam, and Tokyo, we're making the world safer through proactive AI-based alerts and powerful retrospective analysis tools. The Role Join our AI Engineering Team to build data infrastructure and APIs powering intelligent video analytics at global scale. Work on products like Vehicle Surveillance (license plate recognition), Video Search (natural language search through video), POS Integration (transaction-to-video sync), and data pipelines integrating in-house AI models and LLMs/VLMs. What You'll Do • Design and build scalable backend services in Go for cloud video intelligence • Develop data pipelines integrating in-house AI models and LLMs/VLMs to process video insights • Build RESTful APIs for Vehicle Surveillance, Video Search, POS integration • Integrate AI/ML models for license plate recognition, object detection, and semantic video search • Architect event-driven systems using Apache Pulsar • Optimize PostgreSQL and Elasticsearch for transactional and analytical workloads • Collaborate with global teams across Austin, Amsterdam, and Tokyo • Own services end-to-end Required Skills (3-7 Years) • Strong Go programming with production microservices experience • CS fundamentals: data structures, algorithms, distributed systems, concurrency • Kubernetes and Docker experience • PostgreSQL expertise with query optimization • CI/CD and automated deployment pipelines • Strong communication for distributed team collaboration • Analytical problem-solving skills Highly Desired • Apache Pulsar, Kafka, or event-driven architecture • Elasticsearch, Redis, or caching solutions • AI/ML model integration or data pipeline development • Prometheus, ELK, or observability tools • Video surveillance, IoT, or computer vision background Our Tech Stack Languages: Go (primary), Python | Infrastructure: Kubernetes, Docker, AWS | Messaging: Apache Pulsar | Databases: PostgreSQL, Elasticsearch, Redis | Monitoring: Prometheus, Grafana, ELK What We're Looking For Self-starters who take ownership, think analytically, design for scale, and collaborate effectively across teams. Comfortable with ambiguity and translating complex problems into engineering solutions. Why Join Us • Impact: Protect schools, hospitals, and businesses globally • AI-first: Cutting-edge video intelligence at massive scale • Talented team: Skilled, collaborative engineers who value excellence • Autonomy: Propose ideas and influence architecture • Growth: Technical leadership opportunities • Benefits: Comprehensive medical coverage, learning budget Location: Bangalore | Experience: 3-7 years | Type: Full-time Eagle Eye Networks values diversity and welcomes applicants from all backgrounds. Ready to build AI-powered video intelligence at scale? Apply now.
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
- Go (CANONICAL) primary
- Go 1.0 (VERSION)
- Go 1.1 (VERSION)
- Go 1.10 (VERSION)
- Go 1.11 (VERSION)
- Go 1.12 (VERSION)
- Go 1.13 (VERSION)
- Go 1.14 (VERSION)
- Go 1.15 (VERSION)
- Go 1.16 (VERSION)
- Go 1.17 (VERSION)
- Go 1.18 (VERSION)
- Go 1.19 (VERSION)
- Go 1.2 (VERSION)
- Go 1.20 (VERSION)
- Go 1.21 (VERSION)
- Go 1.22 (VERSION)
- Go 1.3 (VERSION)
- Go 1.4 (VERSION)
- Go 1.5 (VERSION)
- Go 1.6 (VERSION)
- Go 1.7 (VERSION)
- Go 1.8 (VERSION)
- Go 1.9 (VERSION)
- Go 1.x (VERSION)
- Golang (VERSION)
- go 1.18 (VERSION)
- go 1.19 (VERSION)
- go 1.20 (VERSION)
- go 1.21 (VERSION)
- go 1.22 (VERSION)
- go latest (VERSION)
- go1.18 (VERSION)
- go1.19 (VERSION)
- go1.20 (VERSION)
- go1.21 (VERSION)
- go1.22 (VERSION)
- go1.x (VERSION)
- golang (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- License
- bsd
- Year introduced
- 2009
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Go appears in many current job descriptions for backend, cloud, and DevOps roles, and is a standard language in Kubernetes, Docker, and cloud-native stacks; strong GitHub and ecosystem adoption signal broad market demand.
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
-
Go Language and Toolchain Catalog dimension db id 367
Library dimension (catalog)
Roles linked in library: Go Backend Developer
-
Programming Languages Catalog dimension db id 1
Library dimension (catalog)
Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer
-
Programming Languages and Scripting Catalog dimension db id 59
Library dimension (catalog)
Roles linked in library: Cyber Security Engineer
-
Programming Languages for ML Systems Catalog dimension db id 39
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
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) |
|
Go Language and Toolchain
go-language-and-toolchain
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | 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) |
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 skipped (dimension not under chosen role) |
Aliases — catalog
- REST (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Api Architecture Style
- Year introduced
- 2000
- Confidence
- 0.88
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: REST is a default API architecture in many job descriptions and is widely supported by major vendors/frameworks; OpenAPI and RESTful endpoints remain standard in hiring pipelines.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 2122
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
API Design and Contracts Catalog dimension db id 3
Library dimension (catalog)
Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer
-
API Interface and Contract Design Catalog dimension db id 289
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
-
Integration Protocols & Standards Catalog dimension db id 271
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Standards, Protocols & Compliance Catalog dimension db id 452
Library dimension (catalog)
Roles linked in library: Engineering Manager, Sitecore Dev
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
API Design and Contracts
api-design-and-contracts
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
API Interface and Contract Design
api-interface-and-contract-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Integration Protocols & Standards
integration-protocols-standards
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Standards, Protocols & Compliance
standards-protocols-compliance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Apache Pulsar (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Event Stream Store
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2016
- Confidence
- 0.88
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Apache Pulsar appears in some streaming/platform JDs, but far less often than Kafka; GitHub and job-market signals show a smaller, specialized adoption footprint rather than broad default use.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 3533
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Asynchronous Messaging and Event Streaming Catalog dimension db id 297
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Scala Backend Developer
-
Messaging and Event Streaming Catalog dimension db id 8
Library dimension (catalog)
Roles linked in library: Backend Developer, Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- PostgreSQL (CANONICAL) primary
- PG 13 (VERSION)
- PG 14 (VERSION)
- PG 15 (VERSION)
- PG 16 (VERSION)
- PostgreSQL 13 (VERSION)
- PostgreSQL 14 (VERSION)
- PostgreSQL 15 (VERSION)
- PostgreSQL 16 (VERSION)
- Postgres 13 (VERSION)
- Postgres 14 (VERSION)
- Postgres 15 (VERSION)
- Postgres 16 (VERSION)
- pg10 (VERSION)
- pg11 (VERSION)
- pg12 (VERSION)
- pg13 (VERSION)
- pg14 (VERSION)
- pg15 (VERSION)
- pg16 (VERSION)
- postgres (VERSION)
- postgresql 10 (VERSION)
- postgresql 11 (VERSION)
- postgresql 12 (VERSION)
- postgresql 13 (VERSION)
- postgresql 14 (VERSION)
- postgresql 15 (VERSION)
- postgresql 16 (VERSION)
- postgresql-16 (VERSION)
- postgresql10 (VERSION)
- postgresql11 (VERSION)
- postgresql12 (VERSION)
- postgresql13 (VERSION)
- postgresql14 (VERSION)
- postgresql15 (VERSION)
- postgresql16 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Relational Database
- Vendor
- PostgreSQL Global Development Group
- License
- other_open
- Year introduced
- 1996
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: PostgreSQL appears in a large share of backend/data engineering job postings and is a default managed option across AWS RDS, GCP Cloud SQL, and Azure Database, indicating broad hiring-pipeline adoption.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 29
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Relational Data Modeling Catalog dimension db id 216
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Fullstack Developer, PHP Backend Developer
-
Relational Database Design Catalog dimension db id 4
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
-
Relational Database Usage Catalog dimension db id 371
Library dimension (catalog)
Roles linked in library: Go Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Usage
relational-database-usage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Elasticsearch (CANONICAL) primary
- ES (VERSION)
- ElasticSearch (VERSION)
- Elasticsearch 6 (VERSION)
- Elasticsearch 6.x (VERSION)
- Elasticsearch 7 (VERSION)
- Elasticsearch 7.x (VERSION)
- Elasticsearch 8 (VERSION)
- Elasticsearch 8.x (VERSION)
- Elasticsearch v6 (VERSION)
- Elasticsearch v7 (VERSION)
- Elasticsearch v8 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Search Datastore
- Vendor
- Elastic NV
- License
- apache_2
- Year introduced
- 2010
- Confidence
- 0.93
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 8.x
Maturity reasoning: Commonly listed in job descriptions for search/log analytics roles and widely deployed in production; Elastic’s docs and ecosystem show sustained adoption rather than sunset or replacement.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 2925
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Magento Search and Indexing Catalog dimension db id 403
Library dimension (catalog)
Roles linked in library: Magento Dev
-
Search and Content Discovery Catalog dimension db id 356
Library dimension (catalog)
Roles linked in library: Drupal Dev, Sitecore Dev
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Magento Search and Indexing
magento-search-and-indexing
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Search and Content Discovery
search-and-content-discovery
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- 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
- 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 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
- Kafka (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Event Stream Store
- Vendor
- Confluent
- License
- apache_2
- Year introduced
- 2011
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Kafka appears in many production JDs for event streaming and data pipelines, and remains a standard platform in cloud/vendor offerings (e.g., Confluent, AWS MSK), indicating broad hiring demand.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 3533
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Asynchronous Messaging and Event Streaming Catalog dimension db id 297
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Scala Backend Developer
-
Messaging and Background Jobs Catalog dimension db id 291
Library dimension (catalog)
Roles linked in library: PHP Backend Developer, Python Backend Developer, Ruby Backend Developer
-
Messaging and Event Streaming Catalog dimension db id 8
Library dimension (catalog)
Roles linked in library: Backend Developer, Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Messaging and Background Jobs
messaging-and-background-jobs
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | — | 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 skipped (dimension not under chosen role) |
|
Magento Caching and Performance
magento-caching-and-performance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Prometheus (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Monitoring Platform
- Vendor
- Cloud Native Computing Foundation
- License
- apache_2
- Year introduced
- 2012
- Confidence
- 0.62
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Prometheus is widely listed in DevOps/SRE job descriptions and is a standard CNCF monitoring stack component, often paired with Grafana for production observability.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 2837
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Backend Observability, Logging, and Diagnostics Catalog dimension db id 388
Library dimension (catalog)
Roles linked in library: Kotlin Backend Developer, Scala Backend Developer
-
Observability and Incident Response Catalog dimension db id 10
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer
-
Observability and Incident Triage Catalog dimension db id 155
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Observability and Operations Catalog dimension db id 143
Library dimension (catalog)
Roles linked in library: Cloud Architect
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Incident Response
observability-and-incident-response
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Incident Triage
observability-and-incident-triage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Operations
observability-and-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- ELK (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Log Analysis Stack
- Vendor
- Elastic NV
- License
- apache_2
- Year introduced
- 2010
- Confidence
- 0.78
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: ELK (Elasticsearch, Logstash, Kibana) appears frequently in observability/logging job postings and is a standard stack in vendor docs and enterprise deployments, indicating broad market adoption.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 1107
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms & Managed Services Catalog dimension db id 221
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer
-
Crash Reporting and Observability Catalog dimension db id 91
Library dimension (catalog)
Roles linked in library: Android Developer, Flutter Developer, Hybrid Mobile Developer, Ionic Developer, Native Mobile Developer, React Native Developer, iOS Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Crash Reporting and Observability
crash-reporting-and-observability
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- LLMs (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Large Language Models
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: LLMs are increasingly listed in job descriptions for AI/ML and product roles, and major vendors (OpenAI, Anthropic, Google) are shipping APIs and platforms, but they are not yet universal across engineering hiring.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- EMERGING
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 903
- 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
- VLMs (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Vision Language Models
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: VLMs are increasingly appearing in AI/ML job descriptions and vendor roadmaps, but they are not yet a universal hiring staple like core ML or Python.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- EMERGING
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1183
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Machine Learning Frameworks
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Machine Learning Frameworks
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Distributed Systems (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Distributed Systems
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common hiring requirement in backend/platform JDs at large tech firms; appears across AWS, Kafka, microservices, and systems roles, with strong GitHub/Stack Overflow activity and no sunset signal.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1035
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
-
Performance and Scalability Tuning Catalog dimension db id 11
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Performance and Scalability Tuning
performance-and-scalability-tuning
|
✓ | — | 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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- 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 |
|---|---|---|---|---|---|---|
| Go | in_db |
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Go | in_db |
Go Language and Toolchain
go-language-and-toolchain
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Go | in_db |
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Go | in_db |
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Go | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Microservices | in_db |
Microservices and Distributed Systems
microservices-and-distributed-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| REST | in_db |
API Design and Contracts
api-design-and-contracts
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| REST | in_db |
API Interface and Contract Design
api-interface-and-contract-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| REST | in_db |
Integration Protocols & Standards
integration-protocols-standards
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| REST | in_db |
Standards, Protocols & Compliance
standards-protocols-compliance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Apache Pulsar | in_db |
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Apache Pulsar | in_db |
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| PostgreSQL | in_db |
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| PostgreSQL | in_db |
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| PostgreSQL | in_db |
Relational Database Usage
relational-database-usage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Elasticsearch | in_db |
Magento Search and Indexing
magento-search-and-indexing
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Elasticsearch | in_db |
Search and Content Discovery
search-and-content-discovery
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| 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) | |
| 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 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) | |
| Kafka | in_db |
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kafka | in_db |
Messaging and Background Jobs
messaging-and-background-jobs
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kafka | in_db |
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | — | 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 skipped (dimension not under chosen role) | |
| Redis | in_db |
Magento Caching and Performance
magento-caching-and-performance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Observability and Incident Response
observability-and-incident-response
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Observability and Incident Triage
observability-and-incident-triage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Observability and Operations
observability-and-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| ELK | in_db |
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| ELK | in_db |
Crash Reporting and Observability
crash-reporting-and-observability
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| LLMs | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| VLMs | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Distributed Systems | in_db |
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Distributed Systems | in_db |
Performance and Scalability Tuning
performance-and-scalability-tuning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Distributed Systems | 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 | AI/ML | type=Machine Learning Frameworks subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Computer Vision | type=Machine Learning Frameworks subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | IoT | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Concurrency | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Eagle Eye Networks is the",
"last_5_words": "retrospective analysis tools."
},
"text": "Eagle Eye Networks is the global leader in cloud video surveillance, delivering AI-powered video intelligence to tens of thousands of businesses across 90+ countries. Headquartered in Austin, Texas, with development teams in Austin, Bangalore, Amsterdam, and Tokyo, we\u0027re making the world safer through proactive AI-based alerts and powerful retrospective analysis tools.",
"word_count": 54
},
"certifications": [],
"company_name": "Eagle Eye Networks",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"SaaS",
"Cloud Services"
],
"domain": "Software \u0026 SaaS Products"
},
"secondary": null
},
"education": [],
"experience": {
"max": 7,
"min": 3,
"raw": "3-7 Years"
},
"job_locations": [
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": null,
"work_mode": "onsite"
}
],
"role": "AI Engineer",
"role_aliases": [
"AI Engineer",
"Machine Learning Engineer",
"Data Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "The Role",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Join our AI Engineering Team",
"last_5_words": "AI models and LLMs/VLMs."
},
"text": "Join our AI Engineering Team to build data infrastructure and APIs powering intelligent video analytics at global scale. Work on products like Vehicle Surveillance (license plate recognition), Video Search (natural language search through video), POS Integration (transaction-to-video sync), and data pipelines integrating in-house AI models and LLMs/VLMs.",
"word_count": 50
},
{
"bullet_count": 8,
"heading": "What You\u0027ll Do",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Design and build scalable",
"last_5_words": "services end-to-end"
},
"text": "\u2022 Design and build scalable backend services in Go for cloud video intelligence\n\u2022 Develop data pipelines integrating in-house AI models and LLMs/VLMs to process video insights\n\u2022 Build RESTful APIs for Vehicle Surveillance, Video Search, POS integration\n\u2022 Integrate AI/ML models for license plate recognition, object detection, and semantic video search\n\u2022 Architect event-driven systems using Apache Pulsar\n\u2022 Optimize PostgreSQL and Elasticsearch for transactional and analytical workloads\n\u2022 Collaborate with global teams across Austin, Amsterdam, and Tokyo\n\u2022 Own services end-to-end",
"word_count": 88
},
{
"bullet_count": 7,
"heading": "Required Skills (3-7 Years)",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Strong Go programming with",
"last_5_words": "problem-solving skills"
},
"text": "\u2022 Strong Go programming with production microservices experience\n\u2022 CS fundamentals: data structures, algorithms, distributed systems, concurrency\n\u2022 Kubernetes and Docker experience\n\u2022 PostgreSQL expertise with query optimization\n\u2022 CI/CD and automated deployment pipelines\n\u2022 Strong communication for distributed team collaboration\n\u2022 Analytical problem-solving skills",
"word_count": 56
},
{
"bullet_count": 5,
"heading": "Highly Desired",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Apache Pulsar, Kafka, or",
"last_5_words": "computer vision background"
},
"text": "\u2022 Apache Pulsar, Kafka, or event-driven architecture\n\u2022 Elasticsearch, Redis, or caching solutions\n\u2022 AI/ML model integration or data pipeline development\n\u2022 Prometheus, ELK, or observability tools\n\u2022 Video surveillance, IoT, or computer vision background",
"word_count": 40
},
{
"bullet_count": 0,
"heading": "What We\u0027re Looking For",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Self-starters who take ownership,",
"last_5_words": "into engineering solutions."
},
"text": "Self-starters who take ownership, think analytically, design for scale, and collaborate effectively across teams. Comfortable with ambiguity and translating complex problems into engineering solutions.",
"word_count": 32
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Go"
},
{
"is_primary": true,
"skill_name": "Microservices"
},
{
"is_primary": true,
"skill_name": "REST"
},
{
"is_primary": true,
"skill_name": "Apache Pulsar"
},
{
"is_primary": true,
"skill_name": "PostgreSQL"
},
{
"is_primary": true,
"skill_name": "Elasticsearch"
},
{
"is_primary": true,
"skill_name": "Kubernetes"
},
{
"is_primary": true,
"skill_name": "Docker"
},
{
"is_primary": true,
"skill_name": "CI/CD"
},
{
"is_primary": false,
"skill_name": "Kafka"
},
{
"is_primary": false,
"skill_name": "Redis"
},
{
"is_primary": false,
"skill_name": "Prometheus"
},
{
"is_primary": false,
"skill_name": "ELK"
},
{
"is_primary": false,
"skill_name": "LLMs"
},
{
"is_primary": false,
"skill_name": "VLMs"
},
{
"is_primary": false,
"skill_name": "AI/ML"
},
{
"is_primary": false,
"skill_name": "Computer Vision"
},
{
"is_primary": false,
"skill_name": "IoT"
},
{
"is_primary": false,
"skill_name": "Distributed Systems"
},
{
"is_primary": false,
"skill_name": "Concurrency"
}
],
"jd_role": {
"display_name": "AI Engineer",
"rationale": null,
"role_aliases": [
"AI Engineer",
"Machine Learning Engineer",
"Data Engineer"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Eagle Eye Networks is the",
"last_5_words": "retrospective analysis tools."
},
"text": "Eagle Eye Networks is the global leader in cloud video surveillance, delivering AI-powered video intelligence to tens of thousands of businesses across 90+ countries. Headquartered in Austin, Texas, with development teams in Austin, Bangalore, Amsterdam, and Tokyo, we\u0027re making the world safer through proactive AI-based alerts and powerful retrospective analysis tools.",
"word_count": 54
},
"certifications": [],
"company_name": "Eagle Eye Networks",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"SaaS",
"Cloud Services"
],
"domain": "Software \u0026 SaaS Products"
},
"secondary": null
},
"education": [],
"experience": {
"max": 7,
"min": 3,
"raw": "3-7 Years"
},
"job_locations": [
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": null,
"work_mode": "onsite"
}
],
"role": "AI Engineer",
"role_aliases": [
"AI Engineer",
"Machine Learning Engineer",
"Data Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "The Role",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Join our AI Engineering Team",
"last_5_words": "AI models and LLMs/VLMs."
},
"text": "Join our AI Engineering Team to build data infrastructure and APIs powering intelligent video analytics at global scale. Work on products like Vehicle Surveillance (license plate recognition), Video Search (natural language search through video), POS Integration (transaction-to-video sync), and data pipelines integrating in-house AI models and LLMs/VLMs.",
"word_count": 50
},
{
"bullet_count": 8,
"heading": "What You\u0027ll Do",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Design and build scalable",
"last_5_words": "services end-to-end"
},
"text": "\u2022 Design and build scalable backend services in Go for cloud video intelligence\n\u2022 Develop data pipelines integrating in-house AI models and LLMs/VLMs to process video insights\n\u2022 Build RESTful APIs for Vehicle Surveillance, Video Search, POS integration\n\u2022 Integrate AI/ML models for license plate recognition, object detection, and semantic video search\n\u2022 Architect event-driven systems using Apache Pulsar\n\u2022 Optimize PostgreSQL and Elasticsearch for transactional and analytical workloads\n\u2022 Collaborate with global teams across Austin, Amsterdam, and Tokyo\n\u2022 Own services end-to-end",
"word_count": 88
},
{
"bullet_count": 7,
"heading": "Required Skills (3-7 Years)",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Strong Go programming with",
"last_5_words": "problem-solving skills"
},
"text": "\u2022 Strong Go programming with production microservices experience\n\u2022 CS fundamentals: data structures, algorithms, distributed systems, concurrency\n\u2022 Kubernetes and Docker experience\n\u2022 PostgreSQL expertise with query optimization\n\u2022 CI/CD and automated deployment pipelines\n\u2022 Strong communication for distributed team collaboration\n\u2022 Analytical problem-solving skills",
"word_count": 56
},
{
"bullet_count": 5,
"heading": "Highly Desired",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Apache Pulsar, Kafka, or",
"last_5_words": "computer vision background"
},
"text": "\u2022 Apache Pulsar, Kafka, or event-driven architecture\n\u2022 Elasticsearch, Redis, or caching solutions\n\u2022 AI/ML model integration or data pipeline development\n\u2022 Prometheus, ELK, or observability tools\n\u2022 Video surveillance, IoT, or computer vision background",
"word_count": 40
},
{
"bullet_count": 0,
"heading": "What We\u0027re Looking For",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Self-starters who take ownership,",
"last_5_words": "into engineering solutions."
},
"text": "Self-starters who take ownership, think analytically, design for scale, and collaborate effectively across teams. Comfortable with ambiguity and translating complex problems into engineering solutions.",
"word_count": 32
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "d9185637-bb55-4d40-a917-b39989c3b685",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
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API 2 — extract-details
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{
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},
{
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{
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]
},
{
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},
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"dimension": {
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"display_name": "Magento Search and Indexing",
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},
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"dimension": {
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"rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
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{
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},
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"rationale": "Kubernetes-native components used to schedule, accelerate, and isolate ML training and serving workloads. This includes GPU enablement and ML-specific controllers rather than generic cluster administration.",
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},
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"display_name": ".NET Backend Developer",
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{
"display_name": "Go Backend Developer",
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{
"display_name": "PHP Backend Developer",
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]
},
{
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"display_name": "CI/CD Pipeline Platforms",
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"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.",
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},
{
"dimension": {
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"rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
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{
"display_name": "ML Engineer",
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]
},
{
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"display_name": "Asynchronous Messaging and Event Streaming",
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"rationale": "Asynchronous communication patterns and broker technologies used to decouple backend services and move work off the request path. Includes queues, pub/sub, event streams, consumer groups, dead-letter queues, and delivery semantics across systems such as Kafka, RabbitMQ, NATS, SQS/SNS, Pulsar, and ActiveMQ.",
"slug": "asynchronous-messaging-and-event-streaming",
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},
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{
"display_name": ".NET Backend Developer",
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"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Magento Caching and Performance",
"id": 404,
"rationale": "Performance tuning specific to Magento storefronts and their rendering pipeline. This includes cache layers, page generation costs, and practical optimizations that preserve upgradeability while improving shopper experience.",
"slug": "magento-caching-and-performance",
"source": "db"
},
"input_skill": "Redis",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Magento Dev",
"id": 231,
"rationale": null,
"role_archetype": "Engineering",
"slug": "magento-dev",
"source": "db"
}
]
}
],
"input_skill": "Redis",
"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": "Prometheus",
"alias_type": "CANONICAL",
"id": 183,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 9,
"display_name": "Prometheus",
"id": 46,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "prometheus",
"sub_category_id": 2837,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Backend Observability, Logging, and Diagnostics",
"id": 388,
"rationale": "Instrumentation and troubleshooting practices used to understand and improve backend service behavior in production and lower environments. This includes logs, metrics, traces, alerting, dashboards, structured logging, distributed tracing, health checks, and root-cause analysis using ecosystem-specific tools such as SLF4J, Logback, Micrometer, OpenTelemetry, Prometheus, Grafana, ILogger, Serilog, and Application Insights.",
"slug": "backend-observability-logging-and-diagnostics",
"source": "db"
},
"input_skill": "Prometheus",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Incident Response",
"id": 10,
"rationale": "Instrumentation and production troubleshooting practices used to keep backend services reliable. Includes logs, metrics, traces, alerting, dashboards, and incident diagnosis.",
"slug": "observability-and-incident-response",
"source": "db"
},
"input_skill": "Prometheus",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Incident Triage",
"id": 155,
"rationale": "Telemetry, alerting, and troubleshooting practices used to diagnose failed builds, broken deployments, and unhealthy release environments. This is a coherent cluster because delivery reliability depends on quickly identifying where the workflow failed.",
"slug": "observability-and-incident-triage",
"source": "db"
},
"input_skill": "Prometheus",
"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": "Observability and Operations",
"id": 143,
"rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
"slug": "observability-and-operations",
"source": "db"
},
"input_skill": "Prometheus",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
]
}
],
"input_skill": "Prometheus",
"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": "ELK",
"alias_type": "CANONICAL",
"id": 2363,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 13,
"display_name": "ELK",
"id": 1468,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "elk",
"sub_category_id": 1107,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms \u0026 Managed Services",
"id": 221,
"rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
"slug": "cloud-platforms-managed-services",
"source": "db"
},
"input_skill": "ELK",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Crash Reporting and Observability",
"id": 91,
"rationale": "Client-side telemetry used to diagnose crashes, hangs, performance regressions, and field issues in iOS apps. iOS engineers use these tools to understand production behavior and prioritize fixes.",
"slug": "crash-reporting-and-observability",
"source": "db"
},
"input_skill": "ELK",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Android Developer",
"id": 4,
"rationale": null,
"role_archetype": null,
"slug": "android-engineer",
"source": "db"
},
{
"display_name": "Flutter Developer",
"id": 74,
"rationale": null,
"role_archetype": "Engineering",
"slug": "flutter-developer",
"source": "db"
},
{
"display_name": "Hybrid Mobile Developer",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "hybrid-mobile-developer",
"source": "db"
},
{
"display_name": "Ionic Developer",
"id": 434,
"rationale": null,
"role_archetype": null,
"slug": "ionic-developer",
"source": "db"
},
{
"display_name": "Native Mobile Developer",
"id": 75,
"rationale": null,
"role_archetype": "Engineering",
"slug": "native-mobile-developer",
"source": "db"
},
{
"display_name": "React Native Developer",
"id": 73,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-native-developer",
"source": "db"
},
{
"display_name": "iOS Developer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "ios-engineer",
"source": "db"
}
]
}
],
"input_skill": "ELK",
"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": "LLMs",
"alias_type": "CANONICAL",
"id": 1829,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "LLMs",
"id": 1193,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "llms",
"sub_category_id": 903,
"typical_lifespan": "EVERGREEN",
"volatility": "EMERGING"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "LLMs",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "LLMs",
"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": "VLMs",
"alias_type": "CANONICAL",
"id": 2522,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "VLMs",
"id": 1576,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "vlms",
"sub_category_id": 1183,
"typical_lifespan": "EVERGREEN",
"volatility": "EMERGING"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "VLMs",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "VLMs",
"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": "AI/ML",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Machine Learning Frameworks",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "ai-ml",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Computer Vision",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Machine Learning Frameworks",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "computer-vision",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "IoT",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"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": "iot",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Distributed Systems",
"alias_type": "CANONICAL",
"id": 2028,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "Distributed Systems",
"id": 1369,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "distributed-systems",
"sub_category_id": 1035,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms",
"id": 20,
"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
"slug": "cloud-platforms",
"source": "db"
},
"input_skill": "Distributed Systems",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Performance and Scalability Tuning",
"id": 11,
"rationale": "Techniques for improving throughput, latency, and resource efficiency in PHP backend services. This includes profiling, query optimization, concurrency limits, memory use, and bottleneck analysis.",
"slug": "performance-and-scalability-tuning",
"source": "db"
},
"input_skill": "Distributed Systems",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"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": "Distributed Systems",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Distributed Systems",
"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": "Concurrency",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"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": "concurrency",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"AI/ML",
"Computer Vision",
"IoT",
"Concurrency"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "AI Engineer",
"id": 13,
"rationale": "Multi-alias tie (3 roles at 1.0) resolved by TIER_B_TITLE: AI Engineer",
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Go",
"tag": "in_db"
},
{
"skill": "Microservices",
"tag": "in_db"
},
{
"skill": "REST",
"tag": "in_db"
},
{
"skill": "Apache Pulsar",
"tag": "in_db"
},
{
"skill": "PostgreSQL",
"tag": "in_db"
},
{
"skill": "Elasticsearch",
"tag": "in_db"
},
{
"skill": "Kubernetes",
"tag": "in_db"
},
{
"skill": "Docker",
"tag": "in_db"
},
{
"skill": "CI/CD",
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"source": "db"
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{
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"roles_from_db": [
{
"display_name": ".NET Backend Developer",
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{
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{
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"source": "db"
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{
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{
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{
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{
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"display_name": "Fullstack Developer",
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{
"display_name": "Go Backend Developer",
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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.