We seek an experienced AI Developer with hands-on expertise in Agentic AI, Langgraph, and Agentic RAG to design, develop, and deploy autonomous AI agents. You'll collaborate with automation architects to integrate agentic workflowspowered by retrieval-augmented generationinto production environments, optimizing for scalability and reliability.
Key Responsibilities
- Develop and deploy agentic AI systems using Langgraph, including multi-agent architectures for complex task orchestration.
- Build, test, and refine AI agents for applications like test automation, data processing, and decision-making pipelines.
- Integrate Langgraph with frameworks such as Langchain, Hugging Face, or Claude models to create robust, stateful agent workflows.
- Optimize agent performance, handling edge cases, memory management, and error recovery in production.
- Optimize agent performance in RAG scenarios, including query routing, chunking strategies, re-ranking, and handling retrieval failures
- Collaborate with DevOps teams to containerize agents (e.g., Docker/OpenShift) and integrate into CI/CD processes.
Qualifications
- 5+ years of experience in AI/ML development, with at least 2 years focused on Agentic AI and Langgraph.
- Proven hands-on experience building Agentic RAG systems (e.g., tool-calling agents with vector stores like Pinecone or FAISS).
- Strong proficiency in Python; experience with Langchain, LlamaIndex, or similar for RAG orchestration.
