Staff Security Engineer (Enterprise AI)

Benefits

• Compensation: We have a simple, flexible, and transparent remote‑first compensation structure so you can make the best decisions for yourself and your family
• Spending Wallets: Access tech, food, lifestyle, and family planning wallets for your expenses
• Supportive Communities: Get involved with our employee resource groups and community groups
• Remote‑first Workforce: If your role is remote, you can set up shop anywhere in your home country
• Generous Time Off: Take the time you need when life happens
• Health Benefits: Get a plan that fits your needs
• Mental Healthcare: Take care of your mind with great mental health programs
• Parental Leave: Birth and non‑birth parents get 18 weeks’ paid leave. Plus, a 4‑week return‑to‑work transition program, at full base pay
• Away Days: We offer 20 company‑wide paid days off— which help our teams collectively pause to recharge
• Learning & Development: Engage in exciting learning programs to level up your growth

You have built AI governance artifacts (acceptable use policy, data‑handling standards, vendor/model risk assessments) and evaluated AI capabilities within SaaS platforms (e.g., Notion AI, Slack AI, Google Workspace AI, GitHub Copilot) as part of vendor reviewsYou can lead cross‑functional initiatives across Security, Engineering, Legal, Privacy, and Compliance and drive them to closure, and communicate effectively with technical and executive audiences. Experience in regulated environments (SOC 2, PCI DSS) and applying IAM to non‑human/agent identities is a plusYou can build security tooling, guardrails, and detections with Python or similar, and deploy cloud services and policy‑as‑code using Infrastructure as Code (Terraform or similar); familiarity with Kubernetes and AWSYou are a seasoned security engineer with hands‑on experience designing, evaluating, and maintaining security architecture for AI/LLM‑based systems, plus deep expertise in enterprise security systems, processes, and controlsYou understand how LLMs and agentic systems are built (RAG, embeddings, fine‑tuning, tool use) and authn/authz models (OAuth2, SAML, service‑account/non‑human identities) for agentic and machine‑to‑machine access, with strong application‑architecture and threat‑modeling fundamentalsYou have practical experience threat modeling and reviewing AI/LLM applications (e.g., against the OWASP Top 10 for LLM Applications) and securing agentic systems and tool‑calling frameworks — MCP servers/clients, tool‑permission models, and agent‑to‑tool trust boundariesYou have experience with enterprise tools for AI visibility and control (e.g., CASB, IDP/Okta) and familiarity with the corporate systems where AI is adopted (OpenAI, Anthropic, GitHub, Google Workspace, Slack, Notion, Jira)