Staff Software Engineer, AI Safety

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to identify and mitigate risks from scientific superintelligence while retaining the core scientific discovery capabilities of the stack. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, safety-focused evaluations, safety systems to mitigate risks, and a research agenda that explores longer-term needs such as oversight of superintelligent scientific systems.

At Lila's AI Safety team, you will build the shared software that helps our team understand and reduce societal risks from scientific AI. Working with researchers, domain scientists and program colleagues, you will turn needs across threat modeling, evaluations, red teaming and mitigation development into reliable tools and systems. You will own engineering work from scoping and prototyping through deployment and ongoing improvement, supporting research across scientific models, agents and automated experimentation.

What You'll Be Building

• Build reusable services, libraries and model/tool integrations that make evaluations, red-teaming campaigns and mitigation experiments repeatable.
• Develop applications that help researchers and scientific experts organize evidence, inspect results, review data and investigate failures.
• Work with safety colleagues to understand research needs and identify shared engineering needs, prioritize useful improvements and turn evolving research workflows into maintainable software.
• Build data pipelines and experiment records that preserve datasets, taxonomies, model versions, configurations and results, making findings traceable and comparisons reproducible.
• Own the reliability and usability of shared safety tools through testing, debugging, monitoring, documentation and continued improvement.
• Collaborate across LILA with our core AI and software engineering teams to share tooling, align on infrastructure, and avoid duplication.

What You'll Need to Succeed

• A track record of independently delivering and maintaining production software, including projects with ambiguous or changing requirements.
• Strong Python and backend engineering skills, with experience designing APIs, working with databases and building dependable data or execution pipelines.
• Experience translating the needs of researchers, domain experts or other technical users into usable tools, and comfort working across services and interfaces.
• Sound engineering judgment in system design, testing and debugging, including practical decisions about reliability, performance and complexity.
• Engineering experience in AI research, AI safety, scientific computing or other settings with rapidly evolving experimental workflows.
• Clear communication and an interest in scientific AI safety, with the ability to understand research context and make informed engineering decisions.

Bonus Points For

• Building safety-specific tooling.
• Building full-stack internal applications, annotation or review tools, or systems for managing experimental evidence.
• Experience with distributed experiment execution, model-serving integrations or isolated environments for agent evaluations.

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range$192,000—$272,000 USD

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.