• Define and execute the Agentic AI & GenAI research and development strategy for HIS products • Lead cross-functional AI science teams to deliver NLU-powered and autonomous AI solutions that enhance product capabilities • Establish partnerships with academic, research, and healthcare organizations to drive innovation • Oversee the development of agent-based AI systems • Advance state-of-the-art NLU and LLM technologies for HIS-specific language models, clinical text understanding, and workflow automation • Ensure models meet the highest standards for accuracy, fairness, explainability, and compliance with healthcare regulations • Build and mentor a team of AI scientists, engineers, and product collaborators • Establish and manage AI model evaluation, validation, and monitoring frameworks • Work closely with product management and engineering to bring innovations from research into production at scale

• Own the builder pipeline: the developers, tinkerers, and AI engineers who want to build on open AI infrastructure. • Help design and run a program of in-person events in cities where open AI builders are already gathering — not just the major hubs. • Identify and cultivate relationships with companies, projects, and organizations who want to build alongside the open AI community — not just sponsor a logo on a banner. • Be present in the online spaces where open-source AI developers actually live: GitHub, Discord, Reddit, Hacker News, and wherever else the conversation is happening. • Help design and run hackathons focused on open AI infrastructure — from format to prizes to what happens after the event ends. • Work closely with the newsletter, social media, and communications team to make sure what's happening in the community shows up in Mozilla's public voice — and vice versa.

• Map global regulatory requirements to specific, measurable technical 'Evidence' within the DotCoAI platform • Design automated workflows that capture model metadata, training logs, and validation results as immutable compliance records • Conduct deep-dive assessments of existing models to identify non-compliance with emerging standards like the EU AI Act • Lead the technical vetting of third-party AI providers and API-based models

• Break models before potential adversaries • Lead technical stress-testing of AI systems • Design and execute adversarial attacks • Build and maintain Continuous Control stack • Partner with Data Scientists for bias remediation