Artificial Intelligence Engineer

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

Good to Have: GitHub Copilot, Claude Code, Codex, AI Governance, AgentOps, Data Engineering/Data Science background.