Role: Senior GenAI / AI-ML Engineer
Experience Range: 6+ Years
Location: Chennai
Mandatory Skillset: Langchain,LangGraph, Python,Fast API,RAG and Generative AI
Required Qualifications
We’re looking for a Senior GenAI / AI-ML Engineer with strong hands-on experience in designing and deploying production-grade Generative AI solutions.
Must-have skills:
- Bachelor’s degree in Computer Science, Data Engineering, AI/ML, or a related field(Master’s preferred).
- 5+ years of experience in AI/ML, with significant hands-on experience in Generative AI and LLM-based applications.
- Strong hands-on experience with Generative AI / Large Language Models (LLMs), including model integration, evaluation, optimization, and deployment.
- Strong expertise in Python and experience building scalable AI applications and services.
- Hands-on experience with LangChain and LangGraph for developing LLM-powered applications, workflows, and AI agents.
- Strong experience building Retrieval-Augmented Generation (RAG) solutions, including document ingestion, chunking, embeddings, retrieval, reranking, context management, and response generation.
- Strong hands-on experience with FastAPI for developing and exposing AI/ML services and APIs.
- Experience working with LLM APIs and model providers such as OpenAI, Azure OpenAI, Hugging Face, Anthropic, Gemini, or equivalent.
- Good understanding of prompt engineering, embeddings, vector search, and LLM evaluation.
- Experience integrating GenAI solutions with SQL/NoSQL databases, vector databases, and enterprise data sources.
- Strong understanding of cloud platforms such as AWS, Azure, or GCP and their AI/ML services.
- Understanding of MLOps, model lifecycle management, deployment, monitoring, and productionization of AI solutions.
- Strong problem-solving, communication, and collaboration skills, with the ability to work with cross-functional teams.
Preferred Skills
- Model Context Protocol (MCP) experience, including building or integrating MCP servers/tools with LLM applications or AI agents.
- Experience developing AI Agents / Agentic AI workflows using LangGraph or similar frameworks.
- Experience with multi-agent systems, tool calling, function calling, and structured outputs.
- Experience with vector databases such as Pinecone, Weaviate, Qdrant, Chroma, Milvus, or FAISS.
- Experience with LLM fine-tuning, LoRA/PEFT, or model optimization.
- Experience with Docker, Kubernetes, CI/CD, and cloud-native deployments.
- Strong understanding of AI security, data governance, responsible AI, and enterprise GenAI architecture.
- Life Sciences / Pharma / Healthcare domain expertise is highly desirable.
- Experience integrating GenAI solutions into production-level enterprise applications.