Agentic AI Engineer/MCP Protocol Engineer

Role Summary

We are seeking an experienced Lead Agentic AI Engineer with 12+ years of overall experience and strong expertise in designing, developing, and deploying enterprise-scale Agentic AI solutions. The ideal candidate will have hands-on experience with Agentic Layer A2A frameworks, MCP Protocol, AI/ML engineering, vector embeddings, prompt engineering, and Azure cloud-native architectures. The role involves building scalable AI agents, orchestrating multi-agent systems, and delivering high-performance AI solutions on Azure.

Key Responsibilities

• Design and develop enterprise-grade Agentic AI and multi-agent solutions using A2A frameworks and MCP Protocol.
• Build and optimize AI/ML solutions leveraging vector embeddings, prompt engineering, and context engineering techniques.
• Develop scalable backend services using Python, Java, and/or Go.
• Implement and manage AI applications on Azure Cloud, including Azure Functions and Azure Container Apps.
• Design and integrate data solutions using Azure AI Search, Redis, Cosmos DB, and related storage services.
• Architect cloud-native, scalable, secure, and high-performance AI platforms.
• Collaborate with cross-functional teams to deliver AI-driven business solutions.
• Ensure solution reliability, performance optimization, monitoring, and operational excellence.
• Follow best practices for software engineering, DevOps, and MLOps.

Required Skills

• years of overall IT experience.
• Hands-on experience with Agentic Layer A2A frameworks and MCP Protocol.
•  AI/ML Engineering, including:
  • Vector Embeddings
  • Prompt Engineering
  • Context Engineering
• 6+ years of programming experience in at least two of:
  • Python
  • Java
  • Go
• Strong experience deploying and managing solutions on Microsoft Azure.
• Experience with:
  • Azure AI Search
  • Redis
  • Cosmos DB
  • Azure Blob Storage (preferred)
  • Apache Iceberg (preferred)
• Expertise in:
  • Azure Functions
  • Azure Container Apps
  • Cloud-native architecture
  • Scalability and performance optimization
• Strong understanding of distributed systems, microservices, and API integrations.

Preferred Qualifications

• Experience with Generative AI, LLMs, RAG, and AI Agent architectures.
• Healthcare domain experience is a plus.
• Experience with MLOps, CI/CD pipelines, and containerization technologies.

Good to Have

• Healthcare industry experience.
• Exposure to enterprise AI governance, security, and compliance frameworks.