Description

You will build and govern agentic AI systems, focusing on multi-node decision models, retrieval-augmented generation (RAG), and semantic search.

This role is on-site.

Responsibilities

• Build agentic AI models using LangChain, LangGraph, and LangSmith, integrating RAG, semantic search, and API calls.
• Implement guardrails, human-in-the-loop workflows, and response verification to prevent hallucinations and improve accuracy.
• Develop proof-of-concepts for agentic AI solutions, leveraging full-stack capabilities across frontend, backend, and DevOps.
• Utilize LLM-assisted coding tools (Cursor AI, Copilot) for systems architecting, troubleshooting, and rapid prototyping.
• Deploy solutions using AWS services (Lambda, S3, ECR) and containerization with Docker.

Required Skills

• 5+ years of experience in AI engineering, with a focus on agentic workflows.
• Strong proficiency with LangChain, LangGraph, and LangSmith ecosystems.
• Experience building RAG pipelines, semantic search, and data extraction from unstructured sources.
• Hands-on experience with OpenAI API, Swarm/Agents_SDK, and fine-tuning models.
• Proficiency in AWS services including Lambda, S3, API Gateway, and ECR.
• Experience with vector databases and state graphs/agentic memory.
• Strong background in full-stack development (frontend, backend, DevOps) to support PoC delivery.
• Familiarity with LLM-assisted coding tools and AI-centered development workflows.

Preferred Skills

• Docker and Kubernetes orchestration.
• Background in AI research and experimentation.

Key Skills

Education

Any Graduate