Job Summary: We are seeking a highly skilled and innovative Senior AI/ML Engineer with strong experience in Generative AI, multi-agent orchestration, and LLM-based system development. You will be responsible for designing, building, and deploying intelligent agent-based architectures using cutting-edge frameworks like LangChain, LangGraph, and AutoGen. This role involves working across the entire product lifecycle — from MVP to production — and integrating these systems with internal tools and platforms such as GitHub, Databricks, and custom UIs. Key Responsibilities: • Design and implement multi-agent LLM systems using frameworks like LangChain, LangGraph, and AutoGen • Develop and scale GenAI solutions, transitioning from MVP to full production deployments • Integrate AI agents with external tools and APIs, including GitHub, Databricks, and frontend/UI interfaces • Set up and optimize Retrieval-Augmented Generation (RAG) pipelines for domain-specific knowledge retrieval • Apply advanced prompt engineering techniques for high-performance LLM applications • Collaborate with data engineers, product managers, and platform teams to deploy AI solutions in production • Monitor and optimize performance, scalability, and reliability of deployed AI agents • Contribute to architectural decisions for AI/ML systems and workflows Requirements: Must-Have: • 5+ years of hands-on experience in AI/ML development, with at least 1+ years in LLMs and GenAI systems • Strong proficiency in Python and experience with LangChain, LangGraph, AutoGen, or similar libraries • Experience with multi-agent orchestration and building collaborative AI workflows • Familiarity with cloud platforms and tools such as Databricks, MLflow, or similar • Experience in designing and implementing RAG pipelines • Deep understanding of LLM capabilities, prompt engineering, and chaining techniques • Ability to integrate AI agents with external services via REST APIs or SDKs Good to Have: • Experience with front-end integration or full-stack development • Exposure to other orchestration tools like CrewAI, Haystack, or Semantic Kernel • Understanding of vector stores and embedding models (e.g., FAISS, Chroma, OpenAI embeddings) • Contributions to open-source AI tools or agent frameworks