Description
Compensation
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this role is $347K – $385K, and total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
About the Team
We build software that helps understand and reduce risks from increasingly capable AI systems. Our work spans cybersecurity, frontier-risk evaluations, and red teaming, with a focus on turning research and testing into practical tools and reliable systems.
We collaborate across research, engineering, and security to investigate model capabilities, identify potential failures, and develop ways to evaluate and improve safeguards.
About the Role
We're looking for a Software Engineer to build the tools and infrastructure that support this work. You'll partner closely with researchers and other engineers to translate evolving questions into useful software,from early prototypes to systems that teams can depend on.
Projects may include backend services, evaluation infrastructure, data pipelines, and internal applications for running tests, investigating model behavior, and reviewing results. This is a general software engineering role with room to contribute across the stack and develop deeper expertise in AI safety and security.
Responsibilities
- Design, build, and maintain software that supports cybersecurity research, frontier-risk evaluations, and red teaming.
- Develop tools and workflows that make it easier to run evaluations, inspect results, and investigate failures.
- Build services, APIs, data pipelines, and interfaces that help researchers work efficiently.
- Turn experimental workflows into reusable, well-tested, and documented systems.
- Own projects from understanding the problem and designing a solution through implementation, deployment, and ongoing operation.
- Improve reliability, performance, observability, security, and usability as needs evolve.
- Collaborate with researchers, security specialists, and engineers to identify useful problems and make practical technical decisions.
Requirements
- Have strong software engineering fundamentals and experience building, shipping, and maintaining production software.
- Are proficient in a general-purpose programming language and comfortable learning unfamiliar tools and systems.
- Have experience in one or more areas such as backend development, full-stack applications, infrastructure, or data systems.
- Can take an open-ended problem, clarify what matters, and deliver a useful solution.
- Balance rapid iteration with maintainable design and operational reliability.
- Communicate clearly and enjoy working with people across technical disciplines.
- Are interested in understanding advanced AI systems and helping address their risks.
- Experience with security, developer tools, research infrastructure, evaluation platforms, distributed systems, or AI applications would be valuable. Prior AI research or cybersecurity experience is helpful but not required.