Director, Agentic AI Governance

General Dynamics Mission Systems, Inc•Scottsdale, AZ

2d•$251,250 - $271,860•Hybrid

About The Position

GDMS operates one of the largest enterprise AI deployments in the defense industry — not as a pilot program, not as a proof of concept, but deeply embedded in how our workforce operates every day. Adoption is broad, active, and accelerating. The governance challenge here is not how to get people to use AI, it is how to continue to keep pace with people who already are. We are looking for a practitioner who has governed AI at scale, in a high-velocity environment, and who understands that the job is to eliminate friction, not add it. You will evolve this function, including from clean-sheet if needed, to design the systems that let our engineers and program teams move at speed, and establish GDMS as an intellectual authority in agentic AI oversight — at one of the most consequential missions in the industry. If your instinct is to build review boards, this role is not for you. If your instinct is to build self-service systems that make the right path the fast path, we want to talk. As the Director, Agentic AI Governance, you will lead the invention and publication of agentic AI governance frameworks, shaping how GDMS approaches autonomous AI at scale. You will own the design of governance mechanisms that measurably reduce decision cycle times, define risk management practices for multi-agent systems, and build competitive advantage through governance that enables rather than constrains. Partnering across Lines of Business and Functions — and in close collaboration with our CISO and IT security organization — you will drive the governance maturity needed for future mission success while keeping GDMS’s AI velocity ahead of the market.

Requirements

10+ years of experience in the AI/ML domain with a focus on governance, deployment enablement, or responsible AI — in environments where speed of adoption was itself a business objective
Bachelor’s degree in a quantitative discipline such as Computer Science, Engineering, Data Science, or Mathematics
Demonstrated track record of accelerating AI adoption at scale— measurable reductions in governance cycle time, increases in use case throughput, or AI deployment velocity improvements across a large organization
Experience governing AI in high-velocity commercial environments where governance latency is itself a competitive variable — technology companies, financial services, cloud providers, or equivalent
Applied, hands-on experience building and operating agentic AI systems, autonomous architectures, and AI pipelines
Deep technical understanding of AI/ML including traditional ML, deep learning, multi-modal models, and agentic AI architectures — sufficient to assess risk with precision rather than defaulting to caution
Proven experience designing and implementing risk tiering frameworks, lightweight review mechanisms, and self-service governance systems
Proven success leading large-scale, complex AI/ML initiatives with cross-functional stakeholders in matrixed organizations
Strong demonstrated technical writing skills tailored to technical, regulatory, and executive audiences
Executive presence with the ability to influence senior leadership, cross-functional peers, and external stakeholders

Nice To Haves

Advanced degree (M.S. and/or Ph.D.) in a relevant technical or research discipline
Background in AI research and emerging technologies
Experience building a governance function from the ground up — defining scope, building a team, and establishing an operating model
Experience implementing technology-enabled governance solutions across multiple industries or global markets
Familiarity with defense mission contexts and the ability to operate effectively within them

Responsibilities

Design and operate lightweight, tiered governance mechanisms that clear AI use cases at speed — with decision turnaround calibrated to risk level, not organizational inertia
Build self-service governance tooling that enables employees to adopt and extend AI capabilities without individual review for low-risk applications
Establish risk tiering frameworks for autonomous decisions and define oversight levels that scale with deployment volume
Define escalation thresholds and human-in-the-loop requirements for agentic AI deployments
Govern the full AI lifecycle — from deployment through ongoing monitoring, model refresh, and retirement — with continuous rather than point-in-time oversight
Define and deliver governance models for multi-agent systems and orchestrated agent ecosystems
Develop governance frameworks for customer- and mission-facing agents, ensuring explainability, accountability, and consent
Define risk management practices specific to autonomous decision-making, including failure mode analysis and behavioral boundaries for agent actions
Create multi-year strategic roadmaps for AI governance aligned to business velocity, mission outcomes, and evolving regulatory expectations
Author research reports and governance frameworks on agentic AI; establish GDMS as a published intellectual authority in the field
Design and publish transformative governance frameworks, maturity models, and operational toolkits adopted across the enterprise
Identify and evaluate emerging governance challenges before they become blockers to deployment
Translate evolving regulatory requirements — domestic and international — into clear, actionable internal policy without creating bureaucratic drag
Build relationships across GDMS Lines of Business and Functions to shape and deliver governance requirements
Partner closely with the CISO and IT security organization on AI-specific risk; integrate governance frameworks with existing security controls without duplicating ownership
Engage executive leadership, cross-functional peers, and external stakeholders with authority and credibility