Security Engineer

AI agents are changing how enterprises operate. Companies want to move fast with MCPs and agents, but they need a way to do it safely.

CodeIntegrity is the platform security teams use to control MCPs and agents, built for companies deploying AI across the enterprise. We raised $5 million from SYN Ventures, Antler, and Boost, and we are a small team, mostly engineers, shipping fast. We are building the infrastructure that will make enterprise AI safe to use.

What You Will Do

You'll find and address security risks in AI agents and the tools and data they connect to. This is a product security role: turn attack research into tested controls that help customers deploy agents safely.

• Model agent threats. Trace how instructions, identities, permissions, and data move between agents, tools, and MCP servers.
• Reproduce real attacks. Investigate prompt injection, data exfiltration, authorization failures, and unsafe tool use with clear, repeatable test cases.
• Build and evaluate controls. Work with software engineers on detections, access policies, and execution isolation. Measure blocked attacks, missed attacks, and false positives.
• Review product security. Assess designs and code, explain the impact of findings, and work with engineers to prioritize and verify fixes.
• Make security testing repeatable. Turn findings into automated evaluations and regression tests, and document the limits of each control.

What We Need

• You have hands-on experience finding and fixing application, API, or cloud security weaknesses.
• You can read production code and write tools or tests to investigate and reproduce a vulnerability.
• You understand authentication, authorization, trust boundaries, and how sensitive data can be exposed.
• You can assess the impact of a finding and explain practical remediation to engineers.
• You're comfortable learning how agents use tools and data, testing assumptions, and measuring whether a security control works.

Nice to have:

• Familiarity with MCP, tool-calling agents, or LLM application security.
• Experience with prompt injection, data exfiltration, sandboxing, or adversarial testing.
• Background in ML security, detection engineering, AppSec, or security product engineering.

What We Offer

We offer a competitive package for people who can move quickly, work with enterprise customers, and help build critical infrastructure for enterprise AI.

• Competitive package. Salary, equity, and benefits aligned with the scope and ownership of the role.
• Time off. Four weeks of paid vacation, paid sick leave, and paid parental leave.
• Professional development. Budget for conferences, courses, and certifications across AI, enterprise software, and security.
• Equipment. A MacBook and the equipment you need to do your best work.
• Health benefits. Comprehensive medical, dental, and vision coverage.
• Retirement savings. 401(k) retirement plan.
• Customer access. Work directly with companies adopting AI in production and see the impact of what you build.