Description

Key Skills: Agentic AI, Agentic Layer A2A Frameworks, MCP Protocol, AI/ML Engineering, Vector Embeddings, Prompt Engineering, Context Engineering, Python, Java, Go, Azure Cloud, Azure AI Search, Redis, Cosmos DB, Azure Functions, Azure Container Apps, Cloud-Native Architecture, Scalability, Performance Optimization, Generative AI, RAG Pipelines, Multi-Agent Systems, LLMOps, MLOps, CI/CD, Model Monitoring

Roles & Responsibilities:

• Build and deploy Agentic AI solutions using Agentic Layer A2A Frameworks and MCP Protocol.
• Apply AI/ML engineering practices including vector embeddings, prompt engineering, and context engineering.
• Design and develop production-grade applications and services using Python, Java, or Go.
• Develop scalable and reliable cloud-native applications following modern architecture principles.
• Deploy and manage applications on Azure Cloud using Azure Functions and Azure Container Apps.
• Integrate and manage AI and data services including Azure AI Search, Redis, and Cosmos DB.
• Design highly scalable systems with a focus on performance optimization and reliability.
• Build and support multi-agent systems, Generative AI use cases, and RAG-based implementations.
• Implement LLMOps/MLOps practices, CI/CD pipelines, and model monitoring frameworks.
• Collaborate with cross-functional teams to deliver AI-driven solutions aligned with business objectives.
• Optimize application performance and ensure efficient resource utilization in cloud environments.
• Ensure solutions align with security, compliance, and regulated data handling requirements when applicable.

Experience Required:

• 4 - 8+ years of experience in AI/ML Engineering, Cloud Engineering, or Software Development.
• Strong hands-on experience in Agentic AI development and A2A frameworks.
• Expertise in vector embeddings, prompt engineering, and context engineering.
• Strong programming experience in Python, Java, or Go.
• Hands-on experience with Azure Cloud services including Azure Functions, Azure Container Apps, Azure AI Search, Redis, and Cosmos DB.
• Experience with cloud-native architecture, scalability, and performance optimization.
• Exposure to Generative AI, RAG pipelines, Multi-Agent Systems, LLMOps, MLOps, and CI/CD practices is preferred.
• Healthcare domain experience and regulated data environment exposure are an added advantage.

Education: Any Graduation

Key Skills

Education

Any Graduate