Role & Responsibilities
Design, build and deploy LLM, GenAI and Agentic AI solutions for enterprise use cases.
Architect and implement RAG-based applications and multi-agent systems.
Develop AI solutions using Python, LangChain and LangGraph.
Work with Microsoft AI Foundry (Must Have) and enterprise AI platforms such as AWS Bedrock, Databricks Mosaic AI, Gemini and Snowflake Cortex.
Integrate AI/Agentic solutions with APIs, cloud platforms and backend systems.
Optimize AI models for performance, accuracy, cost and latency.
Implement production deployments using Docker, Kubernetes and CI/CD.
Apply AI governance, AgentOps and responsible AI practices.
Lead AI solution architecture and multi-agent design for Lead-level positions.
Collaborate with cross-functional teams and communicate solutions effectively to business and technical stakeholders.
Mandatory Skills
Python | GenAI | LLM | Agentic AI | RAG | LangChain | LangGraph | Microsoft AI Foundry | AWS Bedrock | Docker | Kubernetes | CI/CD
Positive to Have: GitHub Copilot, Claude Code, Codex, AI Governance, AgentOps, Data Engineering/Data Science background.