Description

Build and deploy production-grade Agentic AI solutions using multi-agent systems, A2A frameworks, and the MCP protocol.

This role is on-site.

Responsibilities

• Develop agentic AI layers and multi-agent systems using A2A frameworks and MCP protocol.
• Design and implement scalable cloud-native applications using Python, Java, or Go on Azure.
• Build and optimize RAG pipelines, vector embeddings, and context engineering components.
• Deploy and manage services using Azure Functions, Container Apps, AI Search, Redis, and Cosmos DB.
• Implement LLMOps/MLOps practices, CI/CD pipelines, and model monitoring for reliability.

Required Skills

• 5+ years of experience in AI/ML Engineering or Software Development.
• Strong hands-on experience with Agentic AI, A2A frameworks, and MCP Protocol.
• Proficiency in Python, Java, or Go for production-grade application development.
• Experience with Azure Cloud services: Azure Functions, Container Apps, AI Search, Redis, Cosmos DB.
• Expertise in vector embeddings, prompt engineering, and context engineering.
• Understanding of cloud-native architecture, scalability, and performance optimization.
• Knowledge of Generative AI, RAG pipelines, and multi-agent system design.
• Familiarity with LLMOps, MLOps, CI/CD, and model monitoring frameworks.

Preferred Skills

• Experience in healthcare domain or regulated data environments.

Key Skills

Education

Any Graduate