GenAI / Agentic AI Developer

Key Responsibilities

• Design, develop, and deploy GenAI and Agentic AI applications.
• Build AI agents using LangGraph, AutoGen, CrewAI, or similar frameworks.
• Develop RAG-based applications, LLM solutions, and multi-agent systems.
• Translate business requirements into scalable AI solutions.
• Work with engineering and data teams to deliver production-ready solutions.
• Deploy and scale AI applications using cloud, Docker, Kubernetes, and CI/CD.
• Ensure scalability, security, reliability, and maintainability of AI solutions.

Requirements

• 7+ years of experience in AI/ML, with strong hands-on experience in GenAI/LLM/Agentic AI.
• Strong proficiency in Python.
• Hands-on experience with RAG, LLMs, prompt engineering, embeddings, and vector databases.
• Experience with LangGraph, AutoGen, CrewAI, or similar Agentic AI frameworks.
• Experience with OpenAI, Azure OpenAI, LLaMA, Anthropic, or similar LLM platforms.
• Strong experience in developing and deploying production-grade AI applications.
• Good understanding of APIs, microservices, cloud, and distributed systems.

Domain & Cloud Experience Mandatory

• HCLS: Healthcare / Life Sciences domain experience with Azure is mandatory.
• BFSI: Banking / Financial Services / Insurance domain experience with AWS is mandatory.
• Experience in both HCLS + BFSI with Azure + AWS will be an added advantage.

Good to Have

• MLOps / LLMOps experience.
• Docker, Kubernetes, CI/CD.
• Kafka / RabbitMQ.
• Terraform / CloudFormation.
• Experience with AI monitoring and observability.