- Build and continuously improve the backlog of AI opportunities across R&D, helping teams identify, prioritize, and sequence high-value work.
- Take ambiguous problems from discovery through delivery, including understanding workflows, exploring options, designing solutions, coordinating implementation, testing, documenting, launching, measuring, and improving.
- Design AI-native solutions, choosing among prompts, workflows, integrations, agents, databases, and custom applications.
- Help R&D get more value from enterprise AI tools such as Glean and Claude, partnering with IT and InfoSec on access, configuration, connectors, enablement, and support.
- Own the lifecycle of portfolio AI systems, including automations, skills, agents, and internal web applications.
- Establish practical approaches to evaluation, testing, reliability, observability, security, and maintenance.
- Partner with R&D teams to uncover needs, unblock delivery, clarify ownership, and engage relevant experts.
- Help run and evolve R&D AI governance and enablement practices, improving visibility into active work, risks, adoption, and outcomes.
- Work with Finance and other partners to improve visibility into AI tool usage, spend, and value.
- Explore and support autonomous agents that improve work across the product development lifecycle.