Head of Engineering (Frontier Safety)

New

FAR.AIAI safety

Remote globally., Some timezone flexibility is expected; the current division spans North America, Europe, and Asia-Pacific.Full-TimeManager

Salary$225,000-$350,000/year depending on experience and location, with the potential for additional compensation for exceptional candidates.

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Job Details

Strong track record in software engineering, AI, or another computer engineering discipline, such as cybersecurity or MLOps.
Experience managing, growing, and leading technical teams, including building startups and managing managers.
Experience with relevant parts of the technology stack, such as Python, LLM APIs, local LLM frameworks, evaluation frameworks, cloud infrastructure, and compute clusters.
Experience with coding agents, such as Claude Code, Codex, or Cursor, is relevant to the role.
Ability to thrive in rapidly evolving environments.
Demonstrated drive for mission and impact on frontier AI systems.
Ability to communicate technical solutions to technical and non-technical audiences.
Demonstrated persistence in achieving ambitious goals.
Preferred: experience building, red-teaming, or evaluating frontier LLMs or agentic systems, or building safeguards for them.
Preferred: experience in adversarial machine learning, security, or discovering high-severity vulnerabilities.
Preferred: collaboration with AI labs, security teams, or government safety institutes.
Preferred: published work in AI safety, security, or robustness.

Build and scale red-teaming tools and products to improve the speed, coverage, and importance of findings.
Operationalize systems for attacker simulation and output severity evaluation.
Maintain and evolve vulnerability databases, statistical analysis tools, and reporting infrastructure.
Develop agentic systems for automated red-teaming, jailbreak discovery and integration, and workflow automation.
Build, test, and refine sandboxing architecture for evaluating advanced AI systems in high-stakes risk domains.
Extend infrastructure and tooling for CBRN and cyber evaluations and loss-of-control testing.
Design architecture for external platform contributions and integrations with the AI evaluation ecosystem, including Inspect.
Build and manage an engineering team, mentor team members, and develop hiring pipelines.
Translate division technical priorities into scalable engineering plans, teams, and systems.

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