Senior Director, AI Adoption & Integration

Why RTI

RTI International is an independent, scientific research institute dedicated to improving the human condition. Our vision is to address the world's most critical problems with technical and science‑based solutions in pursuit of a better future. Clients rely on us to answer questions that demand an objective and multidisciplinary approach—one that integrates expertise across social, statistical, data, and laboratory sciences, engineering, and other technical disciplines to solve the world's most challenging problems.

We believe in the promise of science and technical solutions, and we push ourselves every day to deliver on that promise for the good of people, communities, and businesses in the US and around the world. If you are looking for the opportunity to make a real difference, RTI is the place for you.

We are seeking a senior leader to serve as the business unit artificial intelligence lead for RTI Main, a business unit empowered with clear ownership and accountability for developing and executing business strategy, defining market positioning, shaping and evolving the portfolio, making informed investment and operational decisions, and delivering sustainable business performance while proactively managing enterprise and operational risk. The Senior Director, AI Adoption & Integration will be responsible for driving AI adoption and integration across the business unit, translating enterprise AI governance and infrastructure into measurable business outcomes.

This role operates within a matrixed leadership structure that balances business ownership with enterprise AI governance. Reporting directly to the RTI Main Business Unit leadership team, you will be accountable for developing and executing the AI adoption roadmap, driving measurable business and client value, and improving operational outcomes across the business unit. In parallel, you will maintain a matrix reporting relationship to the Office of Data and AI Strategy (ODAS) AI Leader to ensure alignment with enterprise governance, standards, and best practices.

Sitting at the intersection of strategy and execution, this role is responsible for ensuring AI adoption is prioritized, appropriately resourced, and delivering meaningful impact across RTI Main. You will lead and coordinate a network of AI Leads embedded within business functions, fostering collaboration, sharing best practices, and aligning AI initiatives with client needs, scientific priorities, and enterprise strategy while operating within the governance framework established by ODAS.

The ideal candidate is an operating leader who thinks in business outcomes first and AI capabilities second, someone who prioritizes high‑value opportunities, mobilizes cross‑functional teams, and delivers measurable impact y understand that their authority comes from the business, their standards come from ODAS, and their credibility comes from results.

As part of your application, please submit a cover letter describing your interest in the role, how your experience and expertise align with the position's responsibilities, and how your background and career aspirations connect with RTI's mission to improve the human condition through research, innovation, and scientific excellence.

• Develop and own the AI adoption roadmap across RTI Main, translating strategy into prioritized initiatives and measurable outcomes
• Identify and prioritize high‑value AI use cases that drive revenue, efficiency, or client impact
• Lead a portfolio of signature AI initiatives, executed as structured sprints with clear baselines, targets, and accountable owners
• Ensure all initiatives align with ODAS governance, responsible AI guardrails, and Client Technology capabilities

• Operate within ODAS enterprise standards, the approved tool catalog, and responsible AI guidelines—these are the rules of the road, not suggestions
• Populate and maintain Client AI Compliance Registry entries for RTI Main's portfolio—surfacing contract‑specific AI restrictions, disclosure requirements, and data classification constraints upward to…