FAR.AI · Remote (International) · Remote · Posted 28d ago
$225k - $350k
Frontier alignment research to ensure the safe development and deployment of advanced AI systems.
ABOUT US
FAR.AI http://FAR.AI is a non-profit AI research institute working to ensure 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.
We’re structured to support that work from early research through real-world adoption:
Independent by design. We can pursue what's most impactful based on our theory of change and share what we find publicly.
A portfolio approach. Rather than focus on one single direction, we run diverse bets across the safety stack. We take promising ideas from initial experiments to deployment, informed by red-team partnerships with frontier labs and governments.
Serious infrastructure for ambitious research. A dedicated engineering team runs our compute cluster and experiment-scaling stack, so researchers spend their time on research instead of on infra.
Setting the standard. Our events convene key decision makers; our red-team works with frontier developers and governments; and our communications inform the public. Together, this drives adoption and sets the new standard in safety.
Since our founding in July 2022, we've grown to 50+ staff https://www.far.ai/about/team, published 40+ academic papers https://scholar.google.com/citations?user=FVJ24k8AAAAJ, and convened leading AI safety events https://far.ai/events/. Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML including a Best Paper Honorable Mention in 2026 https://icml.cc/virtual/2026/oral/71065, and ICLR, and features in the Financial Times https://www.ft.com/content/175e5314-a7f7-4741-a786-273219f433a1, Nature News https://www.nature.com/articles/d41586-024-02218-7, Wired Magazine https://www.wired.com/story/jailbreaking-ai-models-google-anthropic-openai-spacexai/ and MIT Technology Review https://www.technologyreview.com/2020/02/28/905615/reinforcement-learning-adversarial-attack-gaming-ai-deepmind-alphazero-selfdriving-cars/. We conduct pre-deployment testing on behalf of frontier developers such as OpenAI and independent evaluations for governments including the EU AI Office https://www.far.ai/news/far-ai-selected-to-lead-eu-ai-act-cbrn-risk-consortium and publish the AI Security Leaderboard https://leaderboard.far.ai/ based on our red-teaming expertise. 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 US
FAR.AI http://FAR.AI is a non-profit AI research institute working to ensure 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.
We’re structured to support that work from early research through real-world adoption:
Independent by design. We can pursue what's most impactful based on our theory of change and share what we find publicly.
A portfolio approach. Rather than focus on one single direction, we run diverse bets across the safety stack. We take promising ideas from initial experiments to deployment, informed by red-team partnerships with frontier labs and governments.
Serious infrastructure for ambitious research. A dedicated engineering team runs our compute cluster and experiment-scaling stack, so researchers spend their time on research instead of on infra.
Setting the standard. Our events convene key decision makers; our red-team works with frontier developers and governments; and our communications inform the public. Together, this drives adoption and sets the new standard in safety.
Since our founding in July 2022, we've grown to 50+ staff https://www.far.ai/about/team, published 40+ academic papers https://scholar.google.com/citations?user=FVJ24k8AAAAJ, and convened leading AI safety events https://far.ai/events/. Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML including a Best Paper Honorable Mention in 2026 https://icml.cc/virtual/2026/oral/71065, and ICLR, and features in the Financial Times https://www.ft.com/content/175e5314-a7f7-4741-a786-273219f433a1, Nature News https://www.nature.com/articles/d41586-024-02218-7, Wired Magazine https://www.wired.com/story/jailbreaking-ai-models-google-anthropic-openai-spacexai/ and MIT Technology Review https://www.technologyreview.com/2020/02/28/905615/reinforcement-learning-adversarial-attack-gaming-ai-deepmind-alphazero-selfdriving-cars/. We conduct pre-deployment testing on behalf of frontier developers such as OpenAI and independent evaluations for governments including the EU AI Office https://www.far.ai/news/far-ai-selected-to-lead-eu-ai-act-cbrn-risk-consortium and publish the AI Security Leaderboard https://leaderboard.far.ai/ based on our red-teaming expertise. 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; - Advance state-of-the-art attacker simulation and output harmfulness evaluation; - Maintain and evolve internal vulnerability databases, statistical analysis tools, and reporting infrastructure.
- Build systems to empower high-stakes red-teaming engagements with frontier AI companies and governments: - Support public reports, benchmarks, and leaderboards that shape industry norms - Contribute to red-teaming of frontier models (closed- and open-weight), improving testing systems both within particular engagements and turning insights from engagements into advances in our overall systems; - Build agentic workflows that accelerate the red team broadly.
- Managing, mentoring, and supporting a growing elite team of red-teaming ICs with extremely high standards for velocity, rigor, judgment, and impact; - Plan sprints and lead engineering execution; - Mentor red team ICs in engineering skills, both in direct 1-1 settings and by building resources for rapid skill growth and knowledge transfer; - Manage ICs, supporting and amplifying their impact, setting high standards and prioritization week-to-week, and creating the environment and paths for rapid growth; - Create processes that scale high-tempo engagements without sacrificing quality; - Design and be hiring manager for pipelines to scale the engineering team, in partnership with others on the red team and the org’s recruiting team.
- Contribute to the overall technical and product strategy of the red team;
- Partner closely with the rest of the division to translate technical ideas and findings into real-world impact.
This role would be a great fit if you:
- Are excited by high-stakes, real-world technical work where success is measured by impact, not revenue, clicks, or papers published;
- Want to work with a range of governments, leading AI companies, and academics. We’re a lean organization, and seek to leverage our impact through strategic partnerships;