Senior GenAI Platform Engineer

Qualification: BTech/MTech/MCA
Mode of Work: Hybrid

We're looking for a Senior GenAI Platform Engineer to build
and operate our enterprise AI agent platform — hands-on, in the code, every
day. This is an individual contributor role with no direct reports. You'll
design and build durable asynchronous orchestration, RAG pipelines, and secure
multi-agent workflows on AWS, working alongside a small team of peer engineers.
You'll participate in architecture discussions and code reviews as a strong
technical contributor, not as a manager.

• Build
  AI agents and multi-agent workflows using Amazon Bedrock, Bedrock Agents,
  AgentCore, LangChain, and LangGraph.
  
• Design
  and implement RAG pipelines, prompt engineering strategies, and AI
  guardrails.
  
• Build
  backend services in FastAPI for agent submission, execution, lifecycle
  state machines, and status tracking.
  
• Implement
  queue-based dispatch and durable state stores, ensuring idempotency,
  retries, and failure recovery.
  
• Write
  Infrastructure as Code (Terraform) to provision and manage agent
  infrastructure on AWS.
  
• Integrate
  agents with vector databases, enterprise messaging systems, and internal
  workflow tools.
  
• Instrument
  services for observability — structured logging, tracing, metrics.
  
• Participate
  in code reviews and architecture discussions as a peer contributor.
  
• Write
  clear technical documentation (design docs, runbooks) for systems you
  build.
  

Requirements

• Expert-level
  Python, with strong experience building REST APIs (FastAPI preferred).
  
• Hands-on
  experience with LLMs, Amazon Bedrock (Agents & AgentCore), LangChain,
  LangGraph, RAG, and vector databases.
  
• Strong
  experience with core AWS services: Lambda, ECS/EKS, API Gateway, S3,
  RDS/PostgreSQL.
  
• Working
  proficiency in Terraform and Docker.
  
• Experience
  with CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins).
  
• Solid
  understanding of asynchronous programming and event-driven architectures
  (Kafka or SQS).
  
• Experience
  with modern authentication patterns (OAuth2, OIDC, JWT) and AWS IAM.
  
• Programming: Python , FastAPI
  
• Generative AI: Amazon Bedrock, Bedrock
  Agents, AgentCore, LangChain, LangGraph, Prompt Engineering,
  Retrieval-Augmented Generation (RAG), AI Guardrails, Multi-Agent Systems
  
• Vector Databases: Pinecone, Amazon
  OpenSearch Vector Engine, FAISS, ChromaDB, pgvector
  
• Infrastructure as Code: Terraform, AWS
  CloudFormation (preferred exposure)
  
• Containers & Orchestration: Docker
  
• Databases: PostgreSQL, DynamoDB
  
• Event-Driven Architecture: Amazon SQS,
  Apache Kafka
  
• Authentication & Security: OAuth 2.0,
  OpenID Connect (OIDC), JWT, AWS IAM, Enterprise Identity Integration (Microsoft
  Entra ID)
  
• CI/CD & DevOps:  Git, Automated Deployment Pipelines
  
• Observability: AWS Observability
  
• Software Engineering: System Design,
  Microservices Architecture, Backend Development, API Design, Code Reviews,
  Technical Documentation, Design Documents, Runbooks
  
• Development Practices: Unit Testing,
  Integration Testing, Code Quality, Secure Coding Practices, Agile/Scrum
  

Benefits