Senior Security Engineer - Enterprise AI

Faire•San Francisco, CA

51d•$174,500 - $240,000•Hybrid

About The Position

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 Senior Security Engineer focusing on Enterprise AI, you will own the AI platforms Faire runs on and build the technical guardrails that let AI adoption keep accelerating without new exposure. You will have a real voice in how we scale AI safely here, and you will own turning that direction into working systems, standards, and controls.

Requirements

5+ years of experience in security engineering, platform engineering, infrastructure engineering, or IT engineering.
Experience with platform administration and governance more broadly, owning access controls, configurations, and operational health for business-critical platforms at scale.
Proficiency in at least one object-oriented programming language (e.g., Python, Go, Ruby, Java) with the ability to build integrations, tooling, and automations from scratch.
Experience designing scalable internal systems and infrastructure. You solve categories of problems at the platform level rather than building one-off solutions.
Experience with observability or SIEM tooling (e.g., Datadog, Splunk) and building data pipelines for monitoring and compliance.
A track record of owning technical workstreams end to end and landing them, not just scoping them.
The ability to contribute risk assessments and technical recommendations that inform decisions made by leadership.
Strong communication and collaboration skills across technical and non-technical audiences, with a track record of becoming a trusted partner to teams outside your own.

Nice To Haves

Understanding of LLM internals, including transformer architectures, tokenization, context window management, RAG patterns, prompt engineering techniques, and the security risks inherent to each (e.g., prompt injection, data leakage through context, output manipulation).
Prior experience in an AI governance, AI enablement, or AI platform role.
Familiarity with security and compliance considerations specific to AI tooling, such as data residency, DLP policies for AI-generated content, agent access controls, and OAuth scoping for third-party integrations.
Experience supporting engineering teams building agentic workflows or AI product features.
Background in a high-growth or startup environment where the work was 0 to 1.
Experience with AI platform administration and governance specifically, managing platforms such as Claude.ai, Anthropic Console, OpenAI Console, ChatGPT Enterprise, Glean, etc.

Responsibilities

Own administration of Faire's AI platforms, including Anthropic, OpenAI, Portkey, Fireworks, and more, evaluating and enabling features as they launch.
Partner with orgs across the business to control model availability, manage spend, and own MCPs, agentic identity, and audit logging.
Centralize our MCP standards and infrastructure. You'll set the standards for what we launch internally and build or support our most in-demand custom MCPs.
Build the technical guardrails for safe AI use, including LLM guardrails, prompt injection detection, and blast radius controls for autonomous agents.
Serve as a key technical voice when we decide whether a new AI tool clears our security bar, or whether a given class of data belongs in it, creating frameworks and repeatable assessments to scale.
Design and maintain secure experimentation and developer guardrails such as sandboxed environments and custom configurations, letting engineering move fast as new AI coding tools and agents emerge.
Partner with engineering teams building agentic workflows and AI product features, giving them reusable guardrails, reference patterns, and paved roads rather than one-off reviews.
Engineer observability and visibility into our AI usage and spend, capturing platform logs, building usage pipelines and spend dashboards, and alerting that land in the tools teams already use (e.g., Datadog, Snowflake, Mode).
Produce the guidance and best practices that help teams across Faire use AI well, in a form leaders can take back and share with their own orgs.
Stay current with a fast-moving AI landscape and assess new platform features and agent frameworks for security implications and business value.