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.
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