Senior AI/ML Engineer - GenAI & Cloud Solutions

Job Title: Senior AI/ML Engineer - GenAI & Cloud Solutions

Location: Mason, OH & Woodland Hills, CA

Work Mode: On-site

Employment Type: FTE / Contract

Primary Skills (PS)


Agentic AI, MCP Protocol, Azure Cloud, Python, Azure AI Search, Vector Embeddings, Prompt Engineering, LLM, GenAI, Azure Functions.

Job Description


We are seeking an experienced Senior AI/ML Engineer - GenAI & Cloud Solutions to architect, design, and deploy enterprise-scale AI solutions leveraging Generative AI, Agentic AI, and cloud-native technologies. The ideal candidate will have deep expertise in multi-agent AI systems, Azure Cloud, Large Language Models (LLMs), vector databases, and enterprise AI architecture. This role requires strong technical leadership, hands-on engineering, and experience delivering secure, scalable AI solutions within regulated healthcare environments.

Key Responsibilities

• Architect and design scalable, secure, and high-performance AI/ML platforms using Agentic AI frameworks and MCP Protocol.
• Design and develop enterprise-grade GenAI applications utilizing vector embeddings, prompt engineering, context engineering, and Retrieval-Augmented Generation (RAG) techniques.
• Lead end-to-end AI solution development from architecture through deployment and production support.
• Architect, deploy, and optimize AI/ML workloads on Microsoft Azure Cloud.
• Design cloud-native AI architectures using Azure Functions, Azure Container Apps, and microservices.
• Develop scalable data architectures utilizing Azure AI Search, Redis, Cosmos DB, Blob Storage, and Apache Iceberg.
• Build resilient, high-performing distributed AI systems with strong focus on scalability, availability, and cost optimization.
• Fine-tune and optimize Large Language Models (LLMs) for enterprise use cases.
• Ensure AI solutions comply with healthcare regulations including HIPAA, GDPR, and enterprise security standards.
• Mentor engineering teams, conduct architecture reviews, code reviews, and establish engineering best practices.
• Collaborate with Product Owners, Data Scientists, Architects, Compliance, Security, and Operations teams.
• Evaluate emerging AI technologies and integrate innovative GenAI capabilities into enterprise platforms.

Required Skills & Experience

• Strong hands-on experience with Agentic AI frameworks and MCP Protocol for multi-agent orchestration.
• Expertise in Generative AI, Large Language Models (LLMs), Natural Language Models (NLMs), and Applied AI.
• Experience with vector embeddings, prompt engineering, context engineering, and LLM fine-tuning.
• Advanced Python programming skills; Java or Go experience is a plus.
• Strong expertise in Microsoft Azure Cloud architecture and deployment.
• Experience with Azure AI Search, Redis, Cosmos DB, Blob Storage, and Apache Iceberg.
• Strong understanding of cloud-native architecture, containerization, microservices, and serverless computing.
• Experience deploying AI applications using Azure Functions and Azure Container Apps.
• Strong knowledge of distributed systems, scalability, resilience, and performance optimization.
• Experience working in regulated healthcare environments with HIPAA, GDPR, or similar compliance requirements.
• Excellent communication, leadership, mentoring, and stakeholder management skills.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Microsoft Azure Solutions Architect or Azure AI Engineer certifications.
• Contributions to open-source AI/ML projects, technical publications, or patents.
• Experience leading enterprise AI transformation initiatives.

Technical Skills

• Agentic AI
• MCP Protocol
• Generative AI (GenAI)
• Large Language Models (LLMs)
• Natural Language Models (NLMs)
• Vector Embeddings
• Prompt Engineering
• Context Engineering
• Python
• Java (Preferred)
• Go (Preferred)
• Microsoft Azure
• Azure AI Search
• Azure Functions
• Azure Container Apps
• Redis
• Azure Cosmos DB
• Azure Blob Storage
• Apache Iceberg
• Microservices Architecture
• Containerization
• Serverless Computing
• Cloud-Native Architecture
• Performance Optimization
• Healthcare Compliance (HIPAA, GDPR)
• Technical Leadership
• AI Solution Architecture