Senior AI/ML Engineer (GenAI & Cloud Solutions)

Hi , Our client is looking for an Senior AI/ML Engineer (GenAI & Cloud Solutions) for a project and below is the detailed requirement. Job Title: Senior AI/ML Engineer (GenAI & Cloud Solutions) Location: Woodlands, CA Domain: Healthcare / Health Insurance Qualifications & Experience: • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field with 12-15+ years of overall experience in software engineering, AI/ML, and cloud technologies. • 8+ years of experience designing and developing enterprise-scale AI/ML solutions with strong expertise in Generative AI, LLMs, and cloud-native architectures. • Proven experience building and deploying multi-agent AI systems using Agentic AI frameworks, A2A (Agent-to-Agent) architectures, and MCP (Model Context Protocol). • Strong hands-on experience with LLMs, vector embeddings, prompt engineering, context engineering, RAG architectures, and model fine-tuning. • Advanced proficiency in Python with experience building production-grade AI applications, APIs, and microservices. • Strong experience with Azure Cloud services including Azure OpenAI, Azure AI Search, Azure Functions, Azure Container Apps, Cosmos DB, Blob Storage, and related AI/ML services. • Experience designing and implementing scalable, resilient, and secure cloud-native architectures leveraging microservices, serverless computing, containers, and distributed systems. • Hands-on experience with Azure AI Search, Redis, Cosmos DB, Vector Databases, and distributed storage platforms. • Strong understanding of AI/ML lifecycle management, model deployment, monitoring, performance optimization, and governance. • Experience working within Healthcare Payer, Managed Care, Medicare, Medicaid, or Health Insurance environments is highly preferred. • Knowledge of healthcare regulatory requirements including HIPAA, PHI, GDPR, and secure data handling practices. • Experience mentoring engineering teams, conducting architecture reviews, and establishing AI engineering best practices. • Azure AI Engineer Associate, Azure Solutions Architect, or related cloud certifications are highly desirable. • Excellent communication, stakeholder management, problem-solving, and technical leadership skills. Key Responsibilities: • Design and architect enterprise-scale AI/ML solutions leveraging Generative AI, LLMs, Agentic AI frameworks, A2A architectures, and MCP protocols. • Lead end-to-end development of AI applications including RAG implementations, vector embedding pipelines, prompt engineering, context management, and model integration. • Architect, deploy, and optimize AI/ML workloads on Azure Cloud ensuring scalability, reliability, security, and cost efficiency. • Design and implement cloud-native AI platforms using Azure Functions, Azure Container Apps, microservices, and distributed computing architectures. • Develop and optimize data retrieval and storage solutions utilizing Azure AI Search, Redis, Cosmos DB, Blob Storage, and Iceberg-based architectures. • Collaborate with business stakeholders, product teams, data engineers, compliance teams, and operations groups to deliver enterprise AI initiatives. • Ensure AI solutions comply with healthcare security, privacy, and regulatory requirements including HIPAA and GDPR. • Monitor and improve AI system performance, scalability, latency, reliability, and operational efficiency.