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