Gen AI Engineer

About The Role

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.

• Bachelor’s degree in computer science, Information Systems, Engineering, or equivalent practical experience.
• 5–8 years of professional software engineering experience.
• 2+ years of hands‑on experience building GenAI/Agentic AI applications in production.

• Build AI agents and multi‑agent workflows using Amazon Bedrock, Bedrock Agents, Agent Core, Lang Chain, and Lang Graph.
• 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.

• Expert‑level Python, with strong experience building REST APIs (FastAPI preferred).
• Hands‑on experience with LLMs, Amazon Bedrock (Agents & Agent Core), Lang Chain, Lang Graph, 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 (Git Hub Actions, Git Lab 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, Agent Core, Lang Chain, Lang Graph, Prompt Engineering, Retrieval‑Augmented Generation (RAG), AI Guardrails, Multi‑Agent Systems
• Vector Databases:
  Pinecone, Amazon Open Search Vector Engine, FAISS, ChromaDB, pgvector
• Infrastructure as Code:
  Terraform, AWS Cloud Formation (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 )
• CI/CD & Dev Ops:
  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

• AWS Associate or Professional certification.