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.

Since our founding in July 2022, we've grown to 50+ staff , published 40+ academic papers , and convened leading AI safety events . Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML including a Best Paper Honorable Mention in 2026 , and ICLR, and features in the Financial Times , Nature News , Wired Magazine and MIT Technology Review . We conduct pre-deployment testing on behalf of frontier developers such as OpenAI, independent evaluations for governments including the EU AI Office , and publish the AI Security Leaderboard based on our red-teaming expertise. We help steer and grow the AI safety field through developing research roadmaps with renowned researchers such as Yoshua Bengio; running FAR.Labs , an AI safety-focused co-working space in Berkeley housing 40+ members; and supporting the community through targeted grants to technical researchers.

Head of Engineering (Red Team)

FAR.AI is seeking a Head of Engineering (Red Team) to scale one of the world’s most impactful frontier AI red-teaming programs. This role focuses on building the engineering and execution engine that enables and empowers the red team’s work across testing, tools, products, services, and research. The systems and the team you build will enable the division to execute on high-stakes engagements with frontier AI companies and leading governments, provide these stakeholders critical insights and tools, and consistently create the most progress towards safe AI of any red-teaming group globally. This is an opportunity to shape how AI safety is practiced at the frontier, with real impact on industry behavior, governments, public awareness, and global norms.

About Red-Teaming at FAR.AI

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'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 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.

As Head of Engineering (Red Team), you will be the senior technical owner of engineering for the FAR.AI Red Team, reporting to Kellin Pelrine with a dotted line to Edward Yee. You will partner closely with Kellin, the division’s technical lead, translating broader technical strategy and priorities into a world-class engineering organization, systems, and execution. 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 build from there. 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.
• Initially managing, mentoring, and supporting a growing elite team of engineering / 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.
• Identify and execute on the technical and teambuilding opportunities to scale our impact; ○ Proactively identify the engineering bottlenecks limiting the team;
• Design solutions, prioritize problems, and build and drive home solutions;
• Pair closely with Kellin on technical direction, particularly where engineering systems, red-teaming methodology, evaluations, and research intersect; take broad technical goals and turn them into scalable engineering plans, teams, and systems;
• Work closely with and potentially manage the company engagements/testing team, deepening feedback loops between the systems you build that are used in testing, and the testing that develops new ways to improve the systems;
• Hire and manage engineering managers and other roles to scale engineering to meet division needs.
• Contribute to the overall technical and product strategy of the red team;
• Partner closely with the rest of the division to continuously translate technical ideas and findings into real-world impact.

• 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;
• Get energy from working at the frontier of AI and shaping its path forward;
• Identify and build technical solutions to team bottlenecks proactively and at high velocity;
• Enjoy managing and mentoring an elite high-impact and high-performing team;
• Are excited to build a team, identifying the skillsets and roles we need, building new pipelines and assessments for them where existing ones fall short, and working with our recruiters and others on the broader team to recruit top talent globally;
• Are a leader who wants to grow in an entrepreneurial mindset team;
• Are excited to leverage AI agents (e.g., coding agents) at the very frontier of the field, continually building your team’s skills and judgment to achieve superhuman results;
• Enjoy working with mission-driven colleagues to achieve real-world impact;
• Care deeply about AI safety and impacting how advanced AI systems are deployed;
• Are ready to get shit done and willing to do whatever it takes to change the world;
• Thrive in fast-moving, ambiguous environments with shifting threat models and defenses.

• Do not have leadership experience – a Senior Engineer or similar position on our team may be a better fit;
• Want to start with a large team day 1, or for others to manage all hiring. Part of the role is building the team, by identifying and filling the gaps between our existing team members and recruiting pipelines and the new capacity and skills the team needs;
• Want to set technical direction unilaterally. You will own engineering execution and week-to-week sprint planning, and have substantial input on broader technical direction, working to chart it collaboratively with division leadership;
• Want to prioritize open-ended research, academic metrics of success like papers published, or other interests not directly connected to red-teaming success – our Senior Research Engineer position in the Research division may be a better fit;
• Are primarily motivated by equity upside or compensation;

Are not willing to move at the velocity we need / want a slow-moving, highly structured environment with fixed problem definitions. As an organization, we’re planning to double in size in the next 12-18 months, and the red team will grow even faster. A lot will change, so navigating uncertainty is a core part of the role to capitalize on all the opportunities we will encounter.

• Strong candidates for this role typically have many (but not necessarily all) of the following:
• Have a strong track record in software engineering, AI, or another computer engineering discipline (e.g. cybersecurity, MLOps);
• Have a strong track record of managing, growing, and leading technical teams, including both building start-ups (0 → 1) and scale ups (managing managers);
• Have experience with parts of the tech stack we commonly use. For example, coding agents (e.g., Claude Code, Codex, Cursor), Python, LLM APIs (e.g. OpenAI, Anthropic, Google), local LLM frameworks (e.g., vLLM), evaluation frameworks (e.g., Inspect), LLM agents (e.g., OpenClaw), cloud infrastructure (e.g. GCP), compute clusters (e.g. Kubernetes, Slurm), etc.
• Have thrived in rapidly evolving environments;
• Demonstrated drive for mission/impact and desire to create a real impact on frontier AI systems;
• Can effectively communicate technical solutions to both technical and non-technical audiences;
• Demonstrated relentlessness in achieving ambitious goals. It is a plus (but not required) if you have:
• Experience building or red-teaming frontier LLMs or agentic systems;
• Experience building technical teams and products in an entrepreneurial environment;
• Demonstrated ability to discover non-obvious, high-severity vulnerabilities in complex systems;
• Other experience in closely related areas like adversarial ML or security;
• Prior collaboration with AI labs, security teams, or government safety institutes;
• Published work in AI safety, security, or robustness.

Logistics

If based in the USA or Singapore, you will be an employee of FAR.AI (501(c)(3) research non-profit / non-profit CLG). Outside the USA or Singapore, you will be employed via an EOR organization on behalf of FAR.AI or as a contractor.

• Location: Remote globally. We can sponsor US or Singapore visas. The current red team spans North America, Europe, and Asia-Pacific, so some timezone flexibility is expected.
• Hours: Full-time (40 hours/week).
• Compensation: $225,000 to $350,000 per year. Compensation is determined by our salary bands and your level of experience, with adjustments for location. We also pay for work-related travel and equipment expenses, and offer catered lunch and dinner at our office in Berkeley.
• Application process: Apply by submitting a CV and answering our questions around your interest. From there: a short screening call, work tests, interviews, and finally a paid work trial. If you are not available for a work trial we may be able to find alternative ways of testing your fit.

If you have any questions about the role, feel free to contact us at . Otherwise, if you don't have questions, the best way to ensure a proper review of your skills and qualifications is by applying directly via the application form. Please don't email us to share your resume (it won't have any impact on our decision). Thank you!