Engineering Manager (Red Team)

About this role

ABOUT US FAR.AI http://FAR.AI is a non-profit AI research institute dedicated to ensuring advanced AI is safe and beneficial for everyone. Our mission is to facilitate breakthrough AI safety research, advance global understanding of AI risks and solutions, and foster a coordinated global response. Since our founding in July 2022, we've grown quickly to 50+ staff https://www.far.ai/about/team, producing over 40 influential academic papers https://scholar.google.com/citations?user=FVJ24k8AAAAJ, and establishing leading AI Safety events https://far.ai/events/. Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML, and ICLR, and features in WIRED https://www.wired.com/story/jailbreaking-ai-models-google-anthropic-openai-spacexai/, Financial Times https://www.ft.com/content/175e5314-a7f7-4741-a786-273219f433a1, Guardian https://www.theguardian.com/technology/2026/apr/29/meet-the-ai-jailbreakers-i-see-the-worst-things-humanity-has-produced, Washington Post https://www.washingtonpost.com/wp-intelligence/ai-tech-brief/2026/04/02/ai-tech-brief-adam-gleave-farai-safety-regulation/, and MIT Technology Review https://www.technologyreview.com/2020/02/28/905615/reinforcement-learning-adversarial-attack-gaming-ai-deepmind-alphazero-selfdriving-cars/. Additionally, we help steer and grow the AI safety field through developing https://arxiv.org/abs/2405.06624 research https://arxiv.org/abs/2506.20702 roadmaps https://www.researchgate.net/publication/396910034_Open_Technical_Problems_in_Open-Weight_AI_Model_Risk_Management with renowned researchers such as Yoshua Bengio; running FAR.Labs https://www.far.ai/programs/far-labs, an AI safety-focused co-working space in Berkeley housing 40 members; and supporting the community through targeted grants https://www.far.ai/programs/grantmaking to technical researchers. ABOUT RED-TEAMING AT FAR.AI http://FAR.AI FAR.AI http://FAR.AI’s red team is building toward a simple outcome: materially raising the bar for safety and security of the most widely deployed and capable AI systems in the world. We intend to be the tip of the spear in AI safety: the team that consistently finds the failures others miss, resulting in real mitigations, and setting the standard that labs and governments converge on. We also leverage our in-depth understanding of weaknesses in frontier models to advise frontier developers on mitigations, to guide our own research and grantmaking for improving model security, and to inform the public of key AI risks. We are already one of the leading independent red-teaming organizations. Our work has helped most Western frontier model developers improve safeguards through pre- and post-deployment testing (e.g., we have directly influenced safeguards at major frontier developers like OpenAI and Anthropic), and are increasingly embedded in high-leverage government efforts (e.g., leading a consortium building CBRN evaluations for the European Commission/EU AI Office, and collaborating with the UK AI Security Institute). "FAR.AI http://FAR.AI's pre-deployment testing of GPT-5 series models identified failure modes and mitigations, improving the security of our model releases." – Senior Technical Program Manager, OpenAI “FAR.AI http://FAR.AI have been a trusted and thoughtful collaborator for us, and they have progressed the state of frontier red-teaming through research like STACK. We expect this to be a high impact role and are excited to explore collaborations with the successful candidate.” – Xander Davies, Technical Lead, Red Team at UK AISI In 2026, we are scaling from a strong team with standout wins into a new level of impact for any AI red team globally: - Red-teaming all major frontier model releases (closed and open-weight) within days/weeks of release; - Expanding strategic engagements with governments and conducting pre-deployment testing with most frontier labs; - Deepening our testing of key risk areas like CBRN, cyber, and agents, and exploring new ones like AI control and alignment; - Building tools, agents, and insights that raise the global standard for red-teaming. ABOUT THE ROLE As engineering manager on the FAR.AI http://FAR.AI Red Team, you will be the senior technical owner of our engineering, reporting to Kellin Pelrine https://www.far.ai/about/people/kellin-pelrine with a dotted line to Edward Yee https://www.far.ai/about/people/edward-yee. You will build the engineering team and the systems to test critical safeguards of the next generation of AI models. Success looks like vulnerabilities fixed, safeguards strengthened, and global standards shifted – working with leading frontier labs and governments globally to make this happen. Systems your team builds will enable our high-stakes engagements, accelerate cutting-edge AI security research, and create the tools/products/services that let us and our partners red-team the frontier continuously and comprehensively. The current red team will expand in size significantly, and your engineering team will lay the scalable foundation for a relentless and high velocity division to make advanced AI systems safer. We expect this role to start with a small team and include both substantial hands-on engineering and substantial teambuilding and management, e.g., 40% hands-on 60% management. The balance will increasingly evolve towards the management side as we scale the team. In practice, this role spans: - Building a scalable red-teaming engine: tooling, products, services, evals, agents, and a self-improving workflow that multiplies output: - Build and scale internal/external red-teaming tools and products that improve speed, coverage, and severity of findings; - Develop agentic red-teaming systems to automatically and systematically explore the attack space; - Develop agentic systems to identify new public jailbreaks and other releases, and automatically integrate them into our systems; - Adva