Job description

Your Impact at LILA Lila Sciences is building autonomous systems for scientific discovery, and the AI infrastructure behind that work needs security built in from the start. This role sits on the IT & Security team and owns security engineering for Lila's AI and ML systems, from training and inference pipelines to model registries, MCP servers, and agent runtimes. As the senior individual contributor for AI security, you will translate the AI security roadmap into delivered controls, drive vulnerability remediation to closure, and reduce risk across the full AI lifecycle: data, models, pipelines, and agentic systems. The work is hands on, with technical depth across cloud security, supply chain security, and AI-specific threat models. The role is deeply cross-functional. You will partner with AI Platform, AI Research, ML Operations, Science, and AI Safety so security shows up at design time rather than after the fact. Success looks like AI infrastructure that stays continuously compliant, measurable reduction in open risk, and engineering teams that treat security as part of how they build. What You'll Be Building Turn the AI security roadmap into delivered controls with measurable outcomes Design and implement security controls across training and inference pipelines, model registries, MCP servers, and agent runtimes Keep AI infrastructure continuously compliant against internal standards and applicable frameworks Drive vulnerability remediation across AI infrastructure, models, and dependencies to closure with system owners Reduce risk across data, models, pipelines, and agentic systems through threat modeling, control design, and adversarial assessment Partner with AI Platform, AI Research, ML Operations, Science, and AI Safety so security is embedded at design time What You'll Need to Succeed Strong background in security engineering, cloud security, or DevSecOps, with hands-on experience securing production infrastructure Working knowledge of AI/ML systems and the ML lifecycle, plus AI-specific risks such as prompt injection, model and data poisoning, insecure agent tooling, and inference-time threats Experience with software supply chain security and dependency and vulnerability management Experience implementing data security controls (classification, data flow mapping, access control, encryption) in cloud environments Proven ability to partner across engineering teams and drive cross-functional remediation to closure Comfort operating with ambiguity in a fast-moving research environment Bonus Points For Hands-on AWS security experience Experience with SBOM tooling at scale Familiarity with AI governance and assurance frameworks such as NIST AI RMF Experience with MAESTRO-style threat modeling for agentic systems 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 $252,000 — $374,000 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.

Requirements

Must-haves

Your Impact at LILA
What You'll Be Building
Turn the AI security roadmap into delivered controls with measurable outcomes
Design and implement security controls across training and inference pipelines, model registries, MCP servers, and agent runtimes
Keep AI infrastructure continuously compliant against internal standards and applicable frameworks
Drive vulnerability remediation across AI infrastructure, models, and dependencies to closure with system owners
Reduce risk across data, models, pipelines, and agentic systems through threat modeling, control design, and adversarial assessment
Partner with AI Platform, AI Research, ML Operations, Science, and AI Safety so security is embedded at design time
What You'll Need to Succeed
Strong background in security engineering, cloud security, or DevSecOps, with hands-on experience securing production infrastructure
Working knowledge of AI/ML systems and the ML lifecycle, plus AI-specific risks such as prompt injection, model and data poisoning, insecure agent tooling, and inference-time threats
Experience with software supply chain security and dependency and vulnerability management
Experience implementing data security controls (classification, data flow mapping, access control, encryption) in cloud environments
Proven ability to partner across engineering teams and drive cross-functional remediation to closure
Comfort operating with ambiguity in a fast-moving research environment
Hands-on AWS security experience
Experience with SBOM tooling at scale
Familiarity with AI governance and assurance frameworks such as NIST AI RMF
Experience with MAESTRO-style threat modeling for agentic systems

Nice-to-haves

Bonus Points For

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Benefits

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Dental

Vision

Parental Leave