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About the role
- Engineering Manager building scalable tools, agents, and workflows to red-team frontier AI models. Leading FAR.AI’s engineering team to strengthen AI safety and security.
Responsibilities
- Serve as senior technical owner of engineering for FAR.AI’s Red Team
- Build and scale a red-teaming engine encompassing tooling, products, services, evaluations, agents, and self-improving workflows
- Build and scale internal and external red-teaming tools and products to improve speed, coverage, and severity of findings
- Develop agentic systems to systematically explore attack spaces
- Develop agentic systems to identify new public jailbreaks and releases and integrate them into internal systems
- Advance attacker simulation and output harmfulness evaluation
- Maintain and evolve vulnerability databases, statistical analysis tools, and reporting infrastructure
- Build systems supporting high-stakes red-teaming engagements with frontier AI companies and governments
- Support public reports, benchmarks, and leaderboards that influence industry norms
- Contribute to red-teaming closed- and open-weight frontier models
- Build broadly accelerating agentic workflows for the red team
- Manage, mentor, and support a growing team of red-teaming individual contributors
- Plan sprints and lead engineering execution
- Mentor red team ICs through direct one-to-one support and reusable growth resources
- Set standards and priorities and create paths for rapid team growth
- Create processes for high-tempo engagements without sacrificing quality
- Design and manage hiring pipelines for the engineering team
- Contribute to red-team technical and product strategy
- Partner with the division to translate technical ideas and findings into real-world impact
- Report to Kellin Pelrine with a dotted line to Edward Yee
Requirements
- Strong track record in software engineering, AI, or another computer engineering discipline such as cybersecurity or MLOps
- Strong track record of managing, growing, and leading technical teams
- Experience with coding agents such as Claude Code, Codex, or Cursor
- Experience with Python
- Experience with LLM APIs such as OpenAI, Anthropic, or Google
- Experience with local LLM frameworks such as vLLM
- Experience with evaluation frameworks such as Inspect
- Experience with LLM agents such as OpenClaw
- Experience with cloud infrastructure such as GCP
- Experience with compute clusters such as Kubernetes or Slurm
- Experience thriving 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 relentlessness in achieving ambitious goals
- Leadership experience
- Willingness to perform hands-on coding and engineering, especially during the first 6 months
- Willingness to participate in team building and hiring
- Timezone flexibility
- Full-time availability, 40 hours/week
- Experience building or red-teaming frontier LLMs or agentic systems is a plus, not required
- Experience building technical teams and products in an entrepreneurial environment is a plus, not required
- Experience discovering non-obvious, high-severity vulnerabilities in complex systems is a plus, not required
- Hands-on experience in adversarial ML or security is a plus, not required
- Prior collaboration with AI labs, security teams, or government safety institutes is a plus, not required
- Published work in AI safety, security, or robustness is a plus, not required
Benefits
- Additional compensation may be available for exceptional candidates
- Work-related travel expenses covered
- Work-related equipment expenses covered
- Catered lunch and dinner at FAR.AI offices in Berkeley
- Visa sponsorship for the USA or Singapore
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