Principal Enterprise AI Engineer

ZeroFox

7h

About The Position

ZeroFox protects organizations from external threats across the public attack surface, and we're building AI into how the company itself operates, not just what it ships to customers. You'll be the person who makes that real. This is a broad, hands-on engineering role. You'll assess business unit workflows, identify where automation creates real leverage, and build the systems that deliver it, whether that's an agent, a custom tool, an integration, or something simpler. You'll also evaluate whether enterprise data is ready for AI consumption and build the access patterns that close the gap. You'll make the judgment on the right approach for each problem, build it, and see it through to production. Some internal tooling may inform customer-facing capabilities over time, so you'll navigate that boundary as it comes up.

Requirements

• 8+ years of software engineering experience, including production AI/automation systems and custom internal tooling
• Experience assessing enterprise business processes and choosing the right solution: agent, custom tool, integration, or something simpler
• Track record deploying AI agents or automation into enterprise environments where they replaced real manual work
• Hands-on experience with agentic systems: orchestration, state management, tool-calling patterns, human-in-the-loop design
• Experience defining governance or lifecycle processes for AI systems: quality gates, monitoring, audit, human oversight
• Familiarity with enterprise data systems and what it takes to make their data accessible to AI consumers (quality assessment, access patterns, governance)
• Strong software engineering fundamentals across both AI systems and traditional application development

Nice To Haves

• Experience building internal AI platforms or self-service infrastructure that gave non-infrastructure teams safe access to AI capabilities
• Background in cybersecurity, financial services, healthcare, or another regulated industry with high governance expectations
• Experience standing up a new function or practice from scratch in an organization
• Familiarity with navigating the boundary between internal engineering and customer-facing services delivery

Responsibilities

• Assess business unit workflows and identify where automation, agents, or custom tooling create real leverage
• Design and build agents for internal operations: orchestration, tool-calling patterns, escalation paths, and human-in-the-loop gates
• Build custom internal tools, integrations, and infrastructure that support business operations across functions
• Evaluate enterprise data systems for AI readiness: quality, accessibility, governance, and latency. Build the access patterns that make enterprise data usable by AI systems.
• Define the AI application lifecycle for internally-built systems: how artifacts get verified, tested, deployed, and maintained. Establish quality gates between prototype and production.
• Define and enforce AI governance practices: agent permissions, escalation paths, decision audit trails, behavioral monitoring, and the boundary between autonomous action and human oversight
• Build and operate internal AI infrastructure: self-service capabilities, deployment guardrails, observability, and cost management
• Build tools and interfaces that make AI capabilities accessible to non-technical teams, translating business problems into working systems they can use directly

Benefits

• Competitive compensation
• Community-driven culture with employee events
• Regular catered lunches for in-office work; snacks, drinks available daily
• Generous time off
• Comprehensive health benefits & 401(k) plan
• Fun, modern workspace
• Respectful and nourishing work environment, where every opinion is heard and everyone is encouraged to be an active part of the organizational culture

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed
• Number of Employees: 251-500 employees