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About us

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 (Frontier Safety)

FAR.AI is seeking a Head of Engineering for its Frontier Safety division, which runs one of the world’s most impactful frontier AI testing programs. This role focuses on building the engineering and execution engine that enables and empowers the division’s work across testing, evaluations, 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, and provide these stakeholders critical insights and tools, aiming to multiply the world’s rate of progress via testing towards safe AI. 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 The Frontier Safety Division

FAR.AI’s Frontier Safety division exists to materially raise the bar for safety and security of the most 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, converts these into mitigations by frontier developers, and sets the standard that labs and governments converge on. The division grew out of FAR.AI's red team, and is expanding rapidly into loss of control testing, deeper evaluations, and safeguards. From that base, we discover issues, drive their mitigation, and, where a gap in safeguards is blocking a fix, build the missing technical capacity ourselves. What we learn from building and studying safeguards then feeds back into new ways of finding vulnerabilities. We are already one of the leading independent red-teaming organizations globally. We use our understanding of weaknesses in models to advise frontier developers on mitigations, work with governments on building evaluation infrastructure and technical capability, and to guide our own research and grantmaking for improving model security. Our work has helped most Western frontier model developers improve safeguards through pre- and post-deployment testing (e.g., OpenAI, Anthropic, and Google) and pioneered new industry standards (e.g. the FAR.AI Minimal Standard for Safeguards). We are also 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

The Role

As Head of Engineering (Frontier Safety), you will be the senior technical owner of engineering for the FAR.AI Frontier Safety division, 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, evaluate their most dangerous capabilities, and help close the gaps we find. Success for the division looks like new vulnerabilities found, a rapidly accelerating stream of vulnerabilities fixed, and safeguards strengthened. We work with leading frontier labs and governments globally to make this happen. Towards those goals, success for Engineering looks like abundant technical capacity and leverage in a division that aims to scale the level of our testing, research, products, and overall impact by 10-100x or more per year. This means new technical capabilities move rapidly from prototype to robust deployment; infrastructure scales reliably while hiding underlying complexity; and recurring workflows become increasingly autonomous and effective. Systems your team builds will enable our high-stakes engagements, accelerate cutting-edge AI security research, and power the tools, products, and services that let us and our partners red-team and evaluate the frontier continuously and comprehensively. Together, they will form the scalable foundation for a relentless, high-velocity division working to make advanced AI systems safer.

Why are we hiring for this role?

Our division has grown from a red team into a broader frontier safety program, and our engineering capacity has not kept pace. Today, much of our engineering is done by researchers and red-teamers alongside their main work. We are hiring a Head of Engineering to build that function, starting with a small team and growing from there, so that new research reaches production quickly and our testing can grow much faster than our headcount. For the right person, this is a chance to build the engineering behind one of the leading independent AI safety testing efforts almost from the ground up.

Key Responsibilities

We expect this role to start with a small team and build from there. In practice, this role spans:

• Building a scalable technical engine. Your leadership will take our already state-of-the-art red-teaming stack to the next level and extend it to the division's evaluations, loss-of-control testing, and safeguards work, building tooling, products, services, evals, agents, and a self-improving workflow that exponentially multiplies output:
• Build and scale red-teaming tools and products that improve speed, coverage, and importance of findings;
• Operationalize and scale systems that advance state-of-the-art attacker simulation and output severity evaluation;
• Maintain and evolve internal vulnerability databases, statistical analysis tools, and reporting infrastructure;
• Develop agentic systems, including automated red-teaming agents that systematically explore the attack space, agents that identify and automatically integrate new public jailbreaks, and agents that automate workflows to accelerate the division broadly;
• Build, test, and refine sandboxing architecture that enables rapid and thorough evaluation of the strongest AI systems, while ensuring strong security appropriate for high-stakes risk domains like cybersecurity and autonomy;
• Extend our infrastructure and tooling to support the division's CBRN and cyber evaluations and loss-of-control testing;
• Design and implement architecture that enables external contributions to our platform and integration with the AI evaluation ecosystem (e.g., the Inspect framework), while being privacy compliant and minimizing vulnerability exposure;

• Integrate the systems your team builds with the overall division to empower both velocity and quality of testing, leading to high impact private disclosures; public reports, benchmarks, and leaderboards that shape industry norms; and feedback loops that continuously turn insights from real-world outcomes into advances in our overall systems.

• Building a world-leading engineering team. We have a fast-growing elite team of primarily red-teaming and research talent; you will build and manage an engineering team with similarly high standards for velocity, rigor, judgment, and impact, ultimately creating an environment where people can achieve exceptional growth and do their best work:

• Mentor team members in engineering skills, both in direct 1-1 settings and by building resources for rapid skill growth and knowledge transfer;
• Manage team members, supporting and amplifying their impact, setting high standards and prioritization week-to-week, and creating the environment and paths for rapid growth;
• Initially build and manage a team of ICs (partly from a small number of existing engineering-focused team members, partly from hiring), then hire or grow managers over time according to engineering and division needs;

• Design and be hiring manager for pipelines to scale the engineering team, covering ICs, engineering managers, and other roles. Work in partnership with others in the division and the org’s recruiting team to deliver on these pipelines.

• Shaping technical strategy and organization scaling. We have the opportunity to scale our team, tools, and impact at an unprecedented pace for an AI safety organization. You will identify and execute on high-leverage technical and team-building opportunities to make this happen:

• Contribute to the overall technical and product strategy of the division, proactively identifying, prioritizing, and solving engineering bottlenecks;
• Pair closely with Kellin on technical direction, particularly where engineering systems, red-teaming methodology, evaluations, safeguards, 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 and 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;
• Partner closely with the rest of the division and with teams across FAR.AI to continuously translate technical ideas and findings into real-world impact, including building testbeds and tooling that other FAR.AI teams can use in their research.

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;
- Get energy from working at the frontier of AI and shaping its path forward;
- 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;
- Proactively identify and build technical solutions to team bottlenecks 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;
- Thrive in fast-moving, ambiguous environments with shifting threat models and defenses;
- Are ready to get shit done and willing to do whatever it takes to change the world.

This role would be a poor fit if you:
- 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 the division’s tangible impact – 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 Frontier Safety division will grow even faster. A lot will change both internally and externally for the industry as a whole, so navigating uncertainty and pivoting dynamically is a core part of the role to capitalize on all the opportunities we will encounter.

Required Qualifications

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.

Preferred Qualifications

It is a plus (but not required) if you have:
- Experience building, red-teaming, or evaluating frontier LLMs or agentic systems, or building safeguards for them;
- 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.

If you are earlier in your career, we encourage you to consider our other roles within the division. We are likewise also open to more senior versions of this role, simply apply or reach out to talent@far.ai.

Logistics

If you are based in the US, you will be a full-time employee of FAR.AI, a 501(c)(3) nonprofit. If you’re based in Singapore, you will be an employee of FAR.Singapore. If based elsewhere, you will be employed via an Employer of Record. We sponsor visas for in-person employees, and can hire remotely in most countries.

• Location: Remote globally. We can sponsor US or Singapore visas. The current division spans North America, Europe, and Asia-Pacific, so some timezone flexibility is expected.
• Hours: Full-time (40 hours/week).
• Compensation: $225,000-$350,000/year depending on experience and location, with the potential for additional compensation for exceptional candidates. We will also pay for work-related travel and equipment expenses. We offer catered lunch and dinner at our offices 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 talent@far.ai. 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!

Compensation Range: $225K - $350K