Manager, AI Business Support

CAS is building an AI organization that delivers production systems for scientists, customers, and the business. This role sits within the CAS AI team and leads a team of forward-deployed engineers, called AI Business Partners, who bring AI into how CAS and ACS business functions work every day. The manager is first a leader of people and partnerships: someone senior business leaders trust, engineers want to work for, and the organization sees as a visible champion for AI adoption. The manager is also a technical leader, able to direct technical work, ask the right questions, and judge the quality of what the team delivers, drawing on technical colleagues to assess and shape it where needed. The role does not require hands-on development. The role also runs the internal governance process that applies CAS AI policy to business use cases, and leads the AI champion network, which places champions within each business function to spread capability where the work happens.

AI Business Partners are engineers who are part of the CAS AI team and work embedded with business functions. They spend time inside those functions, find the problems worth solving, and design, build, and run AI solutions through to production. Work that becomes shared platform capability, or that serves customers, moves to other parts of the CAS AI team with a written specification, an evaluation plan, and a named business owner.

Champions are members of their own business functions and stay in those roles, with dedicated time for AI work. Champions answer day-to-day AI questions within their functions and build within a defined scope. AI Business Partners take escalations, harder questions, and work that needs engineering depth.

• Build trusted relationships with leaders across CAS and ACS functions and become their first call on AI.
• Make the team the first point of contact for AI questions from business functions, including what tools to use, what is allowed, and how to get started.
• Shape the internal AI use case portfolio. Size each idea by who has the problem, how often, what it is worth, and what mistakes would cost.
• Decide for each use case whether to reuse an existing solution, buy, build, or place it on the backlog, and explain those decisions in business terms.
• Track the value of solutions after launch, and retire solutions that no longer earn their keep.

• Direct the team’s technical work from design through deployment and support, setting priorities, removing obstacles, and keeping delivery on track.
• Set clear expectations for quality, including testing, security, documentation, and supportability, and hold the team to them.
• Judge whether solutions are fit for purpose, and bring in architects, evaluation specialists, and other technical colleagues to assess and shape work where deeper expertise is needed.
• Make sure each solution has defined test cases and quality measures, and make the final call on whether it is ready for users.
• Work with platform, evaluation, and infrastructure colleagues across the CAS AI team so that solutions build on shared platforms and meet engineering and security requirements.
• Decide when a solution should be handed off as shared platform capability, and lead that handoff with a clear specification.

• Serve as the sponsor and organizer of the AI champion network.
• Define and document the champion charter, including expectations, scope, and the time each champion needs, agreed with IT, Information Security, and champions’ managers within each function.
• Set nomination criteria based on demonstrated AI use and peer trust rather than seniority, and confirm managers commit protected time.
• Design champion training around each champion’s own work, with delivery of one real use case from their function as the standard for completion.
• Prepare champions to field AI questions within their functions and teach peers, with clear guidance on when to escalate to the AI Business Partners.
• Lead education for business functions through sessions, demonstrations, office hours, and reusable guides, delivered by the team and by champions.
• Own what happens after training, including ongoing support, regular community activity, manager briefings, and continual renewal of the network.

• Hire, coach, and develop forward-deployed engineers, with growth paths in both technical depth and business partnership.
• Build a team culture of ownership, curiosity, and close partnership with the business.
• Set clear goals, assignments, and standards of quality for the team, and give regular, direct feedback.

• Run the intake and review process that applies CAS AI policy to internal use cases and tool requests.
• Maintain the internal AI use case register, including owners, approved tools, data used, and status.
• Coordinate reviews with Legal, Information Security, Privacy, and Procurement, and track each request to a decision.
• Keep the process fast and predictable, with clear criteria for which requests need full review and which can follow a lighter path.
• Report where policy creates friction or gaps in practice, and bring that feedback to the policy owners.

• Bachelor’s degree in computer science, engineering, a scientific field, business, or a related discipline, or equivalent experience
• Typically 8 or more years of experience in technology, product, consulting, or engineering roles, including 3 or more years leading people
• Experience leading engineers or technical teams, and driving technical work to delivery
• Working knowledge of how AI applications are built, including large language models, agents, and integration with business systems and data, sufficient to direct the work and judge its quality
• Experience working directly with senior business stakeholders to turn problems into delivered solutions
• Strong coaching and people development skills
• Experience teaching or training others, and explaining technical topics to nontechnical audiences

• Prior hands-on experience in software engineering, solutions engineering, or a related technical role
• Experience in a forward-deployed, customer engineering, or embedded consulting team
• Experience running an internal champion, ambassador, or community of practice program
• Experience running a governance, risk, or review process across multiple functions
• Experience in the information industry, scientific publishing, or a scientific organization