Senior Architect, Artificial Intelligence Security - Databricks/Azure/AI

Molina Healthcare•Long Beach, CA

About The Position

Job Summary Provides senior level support for designing, implementing, and maintaining the security framework for Molina’s artificial intelligence and machine learning systems. Serves as the subject matter expert for securing AI/ML workloads operating within Molina’s Microsoft Azure and Databricks environments. Job Duties Designs Secure AI/ML Architectures: Develops and promotes secure, resilient, and scalable architecture patterns for AI/ML solutions built on Microsoft Azure, Databricks, and other platforms. AI/ML Threat Modeling: Conducts 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: Leads 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. AI Tools: Establishes and enforces a comprehensive security and governance framework for our AI tools, such as Model Context Protocol (MCP) servers, ensuring the integrity, confidentiality, and availability of contextual data. MLSecOps Integration: Collaborates 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: Maintains AI Reference Architectures and Guidance and updates the specification and publication of AI Standards and Patterns around AI technology, development, security, privacy, and observability. Strategic Advisory & Business Alignment : Consults on AI capabilities across business and technology platforms, ensuring alignment between AI architecture frameworks and the organization’s strategic goals. Offers actionable recommendations on solution design, risk mitigation, and cross-domain impacts. Partner & Collaborate: Partners with solution architects, technology leaders, business, governance, cyber security, compliance, and privacy teams to identify AI risks, documents design decisions, and provides enterprise patterns to resolve issues. Threat Research: Stays current with the latest threats and vulnerabilities targeting AI systems and develops proactive strategies to defend against them. Designs capabilities for AI Governance and Observability.

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.