Senior Architect, Artificial Intelligence Security - Azure - Remote

Molina Healthcare

18d • Remote

About The Position

We are seeking an experienced and forward-thinking Senior AI Security Architect to join our newly formed AI Security Architecture team. In this critical role, you will be responsible for designing and implementing the security framework for our cutting-edge artificial intelligence and machine learning systems. You will be the subject matter expert for securing AI/ML workloads operating within our Microsoft Azure and Databricks environments. The ideal candidate will have a deep understanding of modern AI architectures, including the unique security challenges presented by GenAI, Agentic AI systems and Model Context Protocol (MCP) servers.

Requirements

• At least 5 years of experience in a senior cybersecurity role (e.g., Security Architect, Cloud Security Engineer), or equivalent combination of relevant education and experience.
• Proven, hands-on experience securing AI/ML workloads and data pipelines within Microsoft Azure and Databricks platforms.
• Deep understanding of the AI/ML lifecycle and MLOps practices.
• Strong understanding of network, application, and data security controls in a cloud-native environment.
• Demonstrated knowledge of the unique security challenges and threat landscape of AI/ML systems.
• Proficient in Python and familiarity with data science and AI libraries.
• Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• Displays intellectual curiosity, integrity, and is motivated by achieving long-term business outcomes.
• Ability to work effectively in a team environment and lead cross-functional teams.

Nice To Haves

• In-depth understanding of Agentic AI security, including common attack vectors and mitigation techniques.
• Experience with Model Context Protocol (MCP) and securing the infrastructure that supports it.
• Familiarity with MLSecOps principles and tools for security testing and automation in for Continuous Integration and Continuous Delivery/Continuous Deployment (CI/CD) pipelines.
• Professional certifications such as Certified Information Systems Security Professional (CISSP), Certified Cloud Security Professional (CCSP), or Azure Security Engineer Associate/Expert.
• Exposure to governance and compliance regimes; a good understanding of security and privacy management, and regulatory requirements including Health Insurance Portability and Accountability Act Health Information Technology for Economic and Clinical Health Act (HIPAA HITECH).
• Experience supporting agile teams by providing guidance on design, opportunities, impact, and risks, taking account of technical and architectural debt.
• Experience designing Generative AI (GenAI) solutions, with experience in Machine Learning Operations (MLOps), Large Language Models (LLM), OpenAI, CoPilot Studio, Agentic AI frameworks such as Langchain, LangGraph and Agent Development Kit (Google ADK), Data Foundry, and Data Fabric.
• Ability to balance the long-term (big picture) and short-term implications of individual decisions.

Responsibilities

• Design Secure AI/ML Architectures: Develop and promote secure, resilient, and scalable architecture patterns for AI/ML solutions built on Microsoft Azure (Azure API Manager, Azure Foundry, Azure OpenAI, CoPilot Studio, etc.) and Databricks (Unity Catalog, notebooks, MLflow, etc.).
• AI/ML Threat Modeling: Conduct comprehensive threat modeling and risk assessments specifically for AI/ML systems, identifying vulnerabilities related to model inversion, data poisoning, adversarial attacks, and prompt injection.
• Agentic AI Security: Lead the threat modeling, risk assessment, and security control design for autonomous AI agents, focusing on mitigating risks such as prompt injection, tool abuse, and uncontrolled agentic behavior.
• MCP Server Governance: Establish and enforce a comprehensive security and governance framework for our Model Context Protocol (MCP) servers, ensuring the integrity, confidentiality, and availability of contextual data.
• MLSecOps Integration: Collaborate with our MLOps and Data Science teams to embed automated security controls ('shift-left') into the entire machine learning development lifecycle, from data ingestion to model deployment.
• Architectural Guidance: Maintain AI Reference Architectures and Guidance and update the specification and publication of AI Standards and Patterns around AI technology, development, security, privacy, and observability.
• Strategic Advisory & Business Alignment: Consult on AI capabilities across business and technology platforms, ensuring alignment between AI architecture frameworks and the organization's strategic goals. Offer actionable recommendations on solution design, risk mitigation, and cross-domain impacts.
• Partner & Collaborate: Partner with solution architects, technology leaders, business, governance, cyber security, compliance, and privacy teams to identify AI risks, document design decisions, and provide enterprise patterns to resolve issues.
• Threat Research: Stay current with the latest threats and vulnerabilities targeting AI systems and develop proactive strategies to defend against them. Design capabilities for AI Governance and Observability.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees