Staff Security Engineer, Enterprise AI

About Faire Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe.

Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement.

If you believe in community, come join ours.

About This Role

The Enterprise Security team at Faire owns the tools and policies that keep our people, data, and systems protected. The team's scope includes endpoint detection, data loss prevention, email security, corporate threat detection, compliance training, and AI governance. As our Staff Security Engineer focusing on Enterprise AI, you will own the AI governance domain within Enterprise Security, serving as IT's technical leader for how Faire adopts, secures, and scales AI.

You'll partner with engineering teams already driving AI initiatives to ensure governance, security, and enablement keep pace with adoption, working across every level of the organization.

What You'Ll Do

Own and drive Faire's company-wide AI strategy in partnership with engineering, business, and executive stakeholders. This means setting the direction for which tools we adopt, how we govern them, and how we scale adoption. Serve as the technical authority on AI platform administration for tools like Anthropic and OpenAI.

You'll evaluate, enable, and disable native connectors, plugins, and features based on risk, security posture, and business value. , risk matrices, enablement criteria) that make AI governance repeatable and transparent. Design and engineer secure experimentation infrastructure, including sandboxed environments, isolated MCP connectors for testing new features, and scoped OAuth flows, so teams can safely explore new AI capabilities.

Requirements (E.G., Overly Broad Permissions, Insufficient Audit Logging)

Lead AI pilot programs end-to-end, from scoping and stakeholder alignment through rollout, troubleshooting, feedback collection, and iteration. Engineer observability and compliance infrastructure, ensuring compliance logs from AI platforms end up in our SIEM. Own the operational mechanics of AI adoption tracking.

) who own their respective adoption metrics. Partner with Learning Development and engineering teams to build and deliver AI training, prompt libraries, and enablement resources tailored to different roles and workflows. Embed with teams across the company to understand their workflows, identify where AI can accelerate their work, and just as importantly, where it shouldn't be used.

Communicate AI strategy, risk trade-offs, and recommendations clearly to audiences ranging from junior engineers to C-level executives, including respectfully challenging perspectives when the data warrants it. , new platform features, agent frameworks) for security implications and business value. What it takes 7+ years of experience in security engineering, platform engineering, infrastructure engineering, or IT engineering.

Experience building and presenting decision frameworks, risk assessments, or strategy recommendations to senior leadership.