Principal Engineer, AI/ML Security

Role overview Set security direction for AI and machine learning systems, while serving as a senior technical authority on AI-related risk. The role combines organization-wide strategy and governance with hands-on work: reviewing product architectures, building security capabilities, testing models against attacks, and translating technical risk for senior decision-makers.

Responsibilities - Define how security controls are built into AI features and customer-facing products, and lead reviews of major initiatives from design through launch. - Own an AI security strategy and multi-year roadmap, prioritizing investments as products and threats evolve. - Establish governance policies, standards, and controls for the responsible development, deployment, and monitoring of AI systems. - Partner with security and data science teams to build, deploy, and monitor models, guardrails, tools, and automations; assess drift and plan improvements. - Lead threat modeling across data ingestion, training, evaluation, model serving, retrieval-augmented generation, agent frameworks, and ongoing monitoring. - Direct adversarial testing, including prompt injection, jailbreaking, evasion, and poisoning, and communicate risk and program decisions to executives and other senior leaders.

Requirements - More than 10 years in cybersecurity, including at least four to five years in AI/ML security, adversarial machine learning, or security data science in a production technology or cloud environment. - Experience owning and driving security or AI programs at an organizational level. - Practitioner-level understanding of adversarial ML attacks and defenses, including evasion, poisoning, model extraction, membership inference, and prompt injection. - Ability to assess AI/ML architecture and turn research into engineering guidance and organizational policy. - Strong Python and Go skills, with experience building security tooling and automation, plus hands-on work with AI red-team, defensive, and model supply-chain tools. - Ability to explain technical AI risks in business terms and guide investment decisions.

Benefits and work setup The role is remote. The source describes professional development support, flexible time off, employee assistance, and potential bonus and equity compensation; specific benefits may vary by location.