AI Engineer-LLM Integration/Platform Observability

Exp -- 4+ Years

2.00 PM to 11:30 PM IST

Mandatory--

hands-on AI Engineer

You will collaborate with cross-functional teams to develop robust, scalable solutions, modernize our logging and monitoring infrastructure, and integrate advanced AI capabilities into production workflows.

Key Responsibilities:

1. LLM Integration & API Development

• Develop and maintain

  LLM API integration test cases

  for core model availability.
• Refactor and reorganize

  LLM API code (e.g., __init__.py)

  for better maintainability.
• Add support for

  Vertex AI batch generation

  and batch transcription processing.
• Implement

  multi-step structured search algorithms

  and tie model IDs to relevant endpoints.
• Explore and integrate emerging technologies like

  LightRAG, SurrealDB, Neo4j, and Puppygraph

  for structured search.

2. Platform Observability & Performance

• Implement

  Splunk OpenTelemetry (OTel)

  integration for monitoring and metrics.
• Evaluate and integrate

  Arize AI

  for observability and model evaluation frameworks.
• Optimize

  logging decorators

  ,

  memory profiling

  for unit tests, and enhance

  APM (Application Performance Monitoring)

  solutions.
• Drive

  scaling and performance optimization

  for the JedAI platform.

3. Platform Integration & Testing

• Implement

  platform integration and availability testing frameworks

  .
• Centralize

  Postman test cases

  for integration testing.
• Clean up

  outdated tests

  and modernize

  Docker Compose setups

  for KB API development.
• Develop

  harness configurations

  for automated testing pipelines.

4. Architecture & Research Spikes

• Support

  JedAI architecture consulting

  efforts.
• Conduct

  spike investigations

  on new technologies and frameworks for performance and scalability.
• Explore

  MCP design

  options for multi-agent orchestration and AI-enhanced workflows.

Required Skills & Experience:

• Programming:

  Python (must-have), Node.js/Java (good to have)

• AI/ML Integration:

  Hands-on experience with

  LLM APIs (OpenAI, Vertex AI, etc.)

• Observability & Logging:

  Experience with

  Splunk, OpenTelemetry (OTel), Arize AI

• Testing & CI/CD:

  Proficiency with

  Postman, Pytest, Docker Compose

• Data & Search:

  Exposure to

  structured search techniques

  (Neo4j, LightRAG, Graph DBs)

• Performance Tuning:

  Familiarity with

  memory profiling, performance optimization, and scaling

  techniques

• Cloud Platforms:

  GCP (Vertex AI), Azure, or AWS experience preferred

• Collaboration Tools:

  GitHub, Jira, Confluence

Preferred Qualifications:

• Bachelor&aposs or Master&aposs in Computer Science, AI/ML, or related fields
• 36 years of experience in AI/ML engineering or platform development
• Prior experience in

  AI observability

  or

  model evaluation pipelines

• Knowledge of

  Agentic AI frameworks

  and

  multi-step reasoning systems