Description

Design and build agentic AI systems using A2A frameworks and MCP protocol.

This role is hybrid.

Responsibilities

• Architect and implement agentic layers using A2A frameworks and MCP protocol.
• Engineer AI/ML solutions with a focus on vector embeddings, prompt engineering, and context engineering.
• Deploy and manage cloud-native solutions on Azure, including Azure Functions and Container Apps.
• Optimize scalability and performance for distributed systems.

Required Skills

• 12+ years of experience in Data Science or Agentic AI.
• 6+ years in AI/ML engineering, specifically vector embeddings, prompt engineering, and context engineering.
• 6+ years programming in at least two of: Python, Java, Go.
• 6+ years deploying solutions on Azure Cloud.
• 6+ years experience with Azure AI Search, Redis, and Cosmos DB (Blob Storage and Iceberg is a plus).
• Strong understanding of cloud-native architecture, scalability, and performance optimization.

Preferred Skills

• Domain experience in healthcare.

Key Skills

Education

Any Graduate