AI Engineer - Agentic AI Solutions
Posted Updated
Summary
AI Engineer (5-8 yrs) in Pune, Chennai, or Bengaluru building end-to-end agentic AI and RAG applications in Python — designing LLM pipelines, multi-agent workflows with LangChain/LangGraph/CrewAI, NLP and vector-database retrieval — with FastAPI, AWS, Docker/Kubernetes, CI/CD and MLOps as pluses.
Key Skills: Vector Database Integration, Retrieval-Augmented Generation, Python, NLP, Generative AI, LangChain Development, MLOps, Kubernetes, System Design, AWS, CICD, Docker
Roles and Responsibilities:
- Design and develop end-to-end agentic AI applications using Python and large language model technologies.
- Build RAG pipelines covering document ingestion, retrieval, context management, and grounded response generation.
- Develop prompt strategies, tool integrations, and multi-agent workflows using LangChain, LangGraph, and CrewAI.
- Apply NLP techniques to improve query understanding, information extraction, classification, and response quality.
- Evaluate, troubleshoot, and refine LLM applications for accuracy, reliability, latency, and production readiness.
Skills Required:
- 5-8 years of relevant experience in AI engineering, machine learning engineering, software engineering, or LLM application development.
- Strong professional experience with Python and production software development.
- Hands-on experience building Generative AI or LLM-powered applications, including RAG solutions and prompt engineering.
- Practical knowledge of NLP, vector databases, embeddings, semantic search, and retrieval workflows.
- Experience with one or more agent orchestration frameworks, including LangChain, LangGraph, or CrewAI.
Good to Have:
- FastAPI, system design, automated testing, AWS, Docker, Kubernetes, CI/CD, MLOps, LangSmith, Langfuse, PyTorch, Hugging Face, PostgreSQL, MongoDB, or Redis.
Education: B.Tech or M.Tech in Computer Science, Artificial Intelligence, Information Technology, or a related discipline.