Manager, Generative AI Advisory and Oversight

Capital One Capital One · Banking · McLean, VA +2

Manager role focused on risk assessment, design reviews, and oversight of AI/ML platforms, specifically Generative AI and Agentic AI systems, within a regulated financial services environment. The role involves collaborating with technical teams to ensure security, reliability, and adherence to risk appetite throughout the AI/ML lifecycle, including defining observability and monitoring requirements for autonomous systems.

What you'd actually do

  1. Provide technical leadership in assessing the architecture, security requirements/controls, roadmaps, and reusable patterns for AI/ML system design and deployments (including Agentic AI frameworks), while providing oversight and effective challenge over the end-to-end AI/ML lifecycle
  2. Evaluate proposed and approved AI/ML technical solutions for automation, resiliency, performance, scalability, and security including appropriate tradeoffs, risks and opportunities
  3. Develop and maintain AI/ML risk guidance to ensure the safe adoption of emerging technologies, including governance for agentic AI components, establishing secure data/tool interaction models and how to maintain secure operational boundaries
  4. Evaluate the dynamic behavior of AI systems and oversee the development of key continuous monitoring controls and testing, ensuring that non-deterministic outputs and autonomous actions remain within risk appetite
  5. Define requirements for AI observability, focusing on the traceability of autonomous decisions and comprehensive system audit trails

Skills

Required

  • Technology Management or Cyber Risk Management experience
  • architecting, designing, developing, integrating, delivering, supporting or assessing complex AI systems
  • Experience assessing GenAI or LLM-Powered application architectures in production
  • security best practices for Generative AI development and deployments

Nice to have

  • deploying scalable and responsible AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud)
  • Master's degree in Computer Science, Computer Engineering, or relevant technical field

What the JD emphasized

  • AI/ML platform and system risk analysis
  • Agentic AI system architectures
  • risk assessments
  • design reviews
  • AI/ML roadmap
  • implementation plan
  • oversight and effective challenge
  • end-to-end AI/ML lifecycle
  • AI/ML technical solutions
  • AI/ML risk guidance
  • agentic AI components
  • AI systems
  • continuous monitoring controls
  • autonomous actions
  • AI observability
  • autonomous decisions
  • Generative AI
  • AI Agents
  • Agentic AI systems
  • GenAI
  • LLM-Powered application architectures
  • security best practices for Generative AI development and deployments

Other signals

  • AI/ML platform and system risk analysis
  • Generative AI platform and Agentic AI system architectures
  • risk assessments, design reviews
  • AI/ML roadmap and implementation plan
  • oversight and effective challenge over the end-to-end AI/ML lifecycle
  • Evaluate proposed and approved AI/ML technical solutions
  • Develop and maintain AI/ML risk guidance
  • governance for agentic AI components
  • secure data/tool interaction models
  • maintain secure operational boundaries
  • Evaluate the dynamic behavior of AI systems
  • continuous monitoring controls and testing
  • Define requirements for AI observability
  • traceability of autonomous decisions
  • comprehensive system audit trails
  • Mentor junior risk associates
  • Generative AI, AI Agents, and Agentic AI systems
  • Build and maintain relationships with technical leaders, engineers, architects
  • assess GenAI or LLM-Powered application architectures in production
  • security best practices for Generative AI development and deployments