Generative AI Engineer – RAG & Lang Chain Systems

We are seeking a highly skilled Generative AI Engineer to design and deploy production-grade AI systems leveraging RAG pipelines, agentic AI workflows, and vector databases. You will work on building scalable, intelligent platforms that integrate LangChain/LangGraph, ADK, and modern LLM orchestration. This role requires strong backend engineering combined with hands-on AI toolchain expertise.ResponsibilitiesArchitect and implement RAG pipelines with hybrid retrieval (dense + BM25), embeddings, and reranking.Build and optimize agentic AI workflows using LangChain/LangGraph, tool orchestration, and multi-agent systems.Design and manage vector storage solutions (FAISS, Pinecone, Chroma, Milvus) for high-performance retrieval.Integrate LLMs (OpenAI, Hugging Face, Groq, etc.) with structured tool calling, multi-turn flows, and guardrails.Collaborate with cross-functional teams to embed AI into enterprise workflows and backend services.Ensure observability, evaluation, and regression testing for AI pipelines to maintain reliability and accuracy.Contribute to prompt engineering, fine-tuning, and ADK-based integrations for domain-specific applications.Required Qualifications3–5+ years of experience in Python backend engineering (FastAPI, Django, Flask).Hands-on expertise with LangChain, LangGraph, ADK, and agentic AI orchestration.Strong knowledge of RAG architectures, embeddings, and vector databases.Experience with cloud platforms (Azure, AWS, GCP) and containerized deployments (Docker, CI/CD).Familiarity with LLM evaluation frameworks and guardrail techniques for safe AI execution.Solid understanding of SQL/NoSQL databases and scalable data pipelines.

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