Senior AI/ML Engineer - GenAI & Cloud Solutions
Diverse Lynx
Senior AI/ML Architect – GenAI & Cloud Solutions
Role: Senior AI/ML Architect – GenAI & Cloud Solutions - 5 Positions Location: Woodland Hills, CA and Mason, OH (Day 1 Onsite) AI/ML, architecture, LLM, python coding Experience: 10+ Year Duration: Long Term Key Skill: AI/ML, architecture, LLM, python coding 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.
- Database s: 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.
Evaluation Criteria (Critical Components)
- Technical Depth
- Ability to design and implement multi-agent AI systems.
- Experience in LLM fine-tuning, embeddings, and context engineering.
- Expertise in coding proficiency with production-grade systems in Python.
- 2. Architectural Vision
- Ability to define enterprise-level AI/ML architecture aligned with cloud-native principles.
- Experience in scalability, resilience, and performance optimization.
- 3. Cloud & Data Expertise
- Hands-on deployment of AI workloads on Azure Cloud.
- Strong knowledge of databases, search systems, and distributed storage.
- 4. Domain Knowledge
- Familiarity with healthcare regulations and ability to design compliant solutions.
- 5. Leadership & Collaboration
- Experience mentoring engineers, conducting reviews, and driving technical excellence.
- Ability to collaborate with cross-functional teams including product, compliance, and operations.
- 6. Innovation & Research Orientation
- Evidence of staying current with GenAI advancements and applying them to real-world problems.
Preferred Qualifications
- Bachelors or master's in computer science, AI/ML, or related field.
- Certifications in Azure Solutions Architect or AI Engineering.
- Publications, patents, or contributions to open-source AI/ML projects.
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