Act as the primary advisor for securing AI/ML workflows, conducting threat modeling for AI product features, and defining guardrails for Large Language Model (LLM) usage
Advise and review on agentic AI usage across the R&D department
Perform security testing and source code review of application and underlying platform for both AI and non-AI systems
Help upskill the wider security and engineering teams on AI security fundamentals and common threats/vulnerabilities
Partner with compliance and legal teams on AI governance decisions and processes
Act as a security partner, building and maintaining relationships with product and engineering teams to integrate security into the development process
Embed security principles and controls to achieve a ‘secure by default’ posture
Secure modern technology stacks that include Kubernetes, Docker, AWS, and CI/CD tooling
Participate in the security engineering on-call rotation to triage and respond to urgent security alerts and incidents outside of standard business hours when necessary

Requirements

Practical experience securing model training and inference pipelines (specifically ARC and MLFlow) and securing AI Gateways
Professional experience as a developer releasing production code, proficient with modern workflows like Agile, GitOps, and CI/CD
Hands-on experience using modern AI development tools (e.g., Cursor, GitHub Copilot, Gemini, or Claude) and interacting with OpenAI/Gemini APIs
Strong foundation in AWS core services, Kubernetes (K8s), Linux systems, and networking principles
Expert-level knowledge of web and AI/ML application security topics (e.g. OWASP Web / LLM / Agent)
Exposure to AI compliance frameworks (e.g. ISO42001)
Experience with architecture reviews, auth protocols flows related to SAML, OAuth2, and OIDC
Deep understanding of the AI ecosystem including design principles, threat models, and appropriate tools
Ability to perform both structured and ad-hoc threat models, providing practical, code-level recommendations that balance security with development speed
Experience working with Ruby on Rails is a plus
Your own unique talents! Unique perspectives and transferable skills are valued at Greenhouse, even if not 100% aligned with the qualifications outlined.

Benefits

Medical, dental, and vision insurance
Basic life insurance
Mental health resources
Financial wellness benefits
Fully paid parental leave program
Short-term and long-term disability coverage
401(k) plan and company match
Up to 14 scheduled paid holidays per calendar year
Up to 80 hours of paid sick leave
Up to 20-25 days of paid vacation time annually based on tenure
Flexible paid time off (PTO)

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

AI securityML workflowsthreat modelingsecurity testingsource code reviewmodel training pipelinesinference pipelinesweb application securityarchitecture reviewsRuby on Rails

Soft skills

advisoryrelationship buildingcommunicationteam collaborationmentoring

Certifications

ISO42001