Description

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

Responsibilities

• Design and build Retrieval Augmented Generation (RAG) pipelines integrating LLMs, vector stores, and knowledge graphs from proof of concept to production.
• Develop and orchestrate multi-step LLM agents and decision-making loops using Lang Graph/Lang Chain.
• Write clean, test-driven Python code for model serving, data pipelines, and microservices.
• Integrate Java services for legacy or latency-critical components via gRPC/REST.
• 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, embedding, 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 with Docker and Kubernetes (GKE/EKS) for service containerization.
• Proficiency in Python, data structures and algorithms, LLMs, LangGraph, LangChain, Java, Microservices, Docker, Kubernetes, Gcp.

Key Skills

Education

Any Graduate