GenAI Agent Engineer

AI overview

Build and optimize core intelligence for autonomous agents using advanced technologies like Bedrock and LangChain while implementing sophisticated RAG pipelines.

The GenAI Agent Engineer will build the core intelligence powering the Agent Runtime and Orchestration layers. They will also design, develop and optimize autonomous and semi-autonomous agents using Bedrock, LangChain/LangGraph, vector search, and structured tool-calling. Responsibilities

Build single and multi-agent systems using LangChain/LangGraph with Bedrock.

Implement RAG pipelines including chunking, embedding, metadata, retrieval tuning, and query rewriting.

Create agent tools such as APIs, SQL queries, and ETL triggers.

Integrate vector databases: OpenSearch, pgvector, Pinecone, Qdrant, DynamoDB vector index.

Implement prompt design and evaluation sets.

Integrate Bedrock APIs, guardrails, and VPC endpoint access.

Qualifications

Strong Python and LangChain/LangGraph engineering.

Production experience with LLM agents and tool calling.

Deep RAG experience.

Familiarity with multiple vector databases.

Strong reasoning-pattern competency.

Minimum Required – in Computer Science, Software Engineering.

Preferred – Advanced coursework or certification in NLP, ML, or AI frameworks.