AI/ML Architect or lead

We need Senior / Lead / Architect level resource with minimum 15+ years of genuine experience.

Role: Senior AI/ML Engineer – GenAI & Cloud Solutions

Key Responsibilities:

• Architect and Design: Lead the design of scalable, secure, and high-performance AI/ML systems leveraging Agentic Layer A2A frameworks and MCP Protocols. 
• Solution Engineering: Drive end-to-end solution development including vector embeddings, prompt engineering, and context engineering for enterprise-grade GenAI applications. 
• Cloud Deployment: Architect and oversee deployment of AI/ML workloads on Azure Cloud, ensuring compliance, scalability, and cost optimization. 
• Data Architecture: Design and optimize data pipelines and storage solutions using Azure AI Search, Redis, Cosmos DB, Blob Storage, and Iceberg. 
• Application Development: Build and manage Azure Functions and Azure Container Apps for microservices-based AI solutions. 
• Performance & Scalability: Define cloud-native architecture patterns, implement performance tuning, and ensure resilience across distributed systems. 
• Domain Expertise: Apply deep knowledge of healthcare domain requirements, ensuring solutions meet regulatory standards (HIPAA, GDPR, etc.) and handle sensitive data securely. 
• Technical Leadership: Mentor engineering teams, establish best practices, and conduct design/code reviews. 
• Innovation & Research: Stay ahead of emerging GenAI, LLM/NLM trends, and integrate cutting-edge approaches into enterprise solutions. 

Required Skills & Expertise:

• Agentic Layer & Protocols: Hands-on expertise with Agentic Layer A2A frameworks and MCP Protocol for multi-agent orchestration. 
• AI/ML Engineering: Strong background in vector embeddings, prompt engineering, context engineering, and fine-tuning LLMs. 
• GenAI & LLM Concepts: Deep understanding of Generative AI, Natural Language Models (NLM), and Large Language Models (LLM). 
• Programming: Advanced proficiency in Python; exposure to Java/Go is a plus. 
• Cloud Proficiency: Strong experience with Azure Cloud services, including deployment, monitoring, and scaling. 
• Databases: Expertise in Azure AI Search, Redis, Cosmos DB; familiarity with Blob Storage and Iceberg is advantageous. 
• Cloud-Native Architecture: Solid grasp of microservices, containerization, serverless computing, scalability, and performance optimization. 
• Healthcare Domain: Experience working with regulated data environments and compliance frameworks.