Description

You will design and build AI solutions powering intelligent applications across Healthcare, BFSI, and Retail.

This role is hybrid.

Responsibilities

• Design and build Retrieval Augmented Generation (RAG) pipelines integrating LLMs, vector stores, and knowledge graphs from PoC to production.
• Develop and orchestrate multi-step LLM agents and decision-making loops using Lang Graph or Lang Chain.
• Write clean, test-driven Python code for model serving, data pipelines, and microservices.
• Containerize and deploy services using Docker and Kubernetes, ensuring scalability and resilience.
• Set up and maintain GitLab CI/CD pipelines for automated testing, security scans, and blue-green deployments.

Required Skills

• 5+ years of professional Python development experience (async, type hints, testing).
• Expertise in LLMs, tokenization, fine-tuning, prompt engineering, and evaluation.
• Hands-on experience building end-to-end RAG systems (vector DBs, embeddings, similarity search, knowledge graph integration).
• Practical experience with LangGraph or LangChain for agentic workflows.
• Strong understanding of data structures and algorithms (hash tables, trees, graphs, heaps).
• Experience integrating Java Services via gRPC/REST.
• Experience with Docker and Kubernetes.
• Proficiency in Agile environment collaboration.

Key Skills

Education

Any Graduate