Lead E2E engineering delivery of CBRNE evaluation pipelines, mitigations, and red-teaming across the model lifecycle; partner with the Portfolio Lead and Program Manager (PM) to ensure critical priorities are addressed while translating ambiguous scientific milestones into technical roadmaps and project plans.
Partner closely with engineers, scientific (SMEs), and the PM to translate complex safety risks and requirements into clear, measurable engineering goals, while driving strategic planning and compute allocation.
Build and guide effective cross-functional partnerships across disciplines, including modeling, infrastructure, evaluation, and release teams, to ensure alignment on objectives and resolve blockers, serving as the operational bridge.
Implement frameworks include OKRs, stand-ups, and agile methodologies to track progress, pre-empt risks, and optimise workflows while fostering a collaborative, interdisciplinary team culture.
Distill complex technical updates into clear, actionable insights for audiences and executive leadership.
Minimum qualifications
Bachelor’s degree in Computer Science, Engineering, Biology, Chemistry, Physics, a related technical/scientific field, or equivalent practical experience.
7 years of experience in technical program management, software engineering, or research engineering.
3 years of experience partnering with research or engineering leads to delivering AI/ML programs, evaluation suites, or safety frameworks.
Preferred qualifications
Master’s degree or PhD in Computer Science, Machine Learning, Biosecurity, Chemistry, or related scientific discipline.
Experience in frontier AI safety, red-teaming methodologies, threat modeling, or dangerous capability evaluations for large language models (LLMs) and autonomous agents.
Experience in a frontier AI lab, national laboratory, government defense, or biosecurity research institution.
Bachelor’s degree in Computer Science, Engineering, Biology, Chemistry, Physics, a related technical/scientific field, or equivalent practical experience.
7 years of experience in technical program management, software engineering, or research engineering.
3 years of experience partnering with research or engineering leads to delivering AI/ML programs, evaluation suites, or safety frameworks.
