Harvey
Staff Software Engineer, Secure Execution
- Employment type
- Full-time
- Workplace type
- Hybrid
- Location
- San Francisco
- Published
- Oct 1, 2026
- Last checked
- Oct 26, 2026
About this role
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
As a Staff Software Engineer on the Security Engineering team, you will join as a founding team member and build the security foundations that let Harvey put increasingly capable AI agents to work. You'll lead development of a platform for agents to perform security work, while shaping how agents are sandboxed across our product and internal platforms.
One of the central challenges is enabling models with advanced cybersecurity capabilities to discover and validate vulnerabilities automatically, including through authorized penetration testing, while protecting sensitive data and systems. You'll build the execution environments, orchestration, and controls that make this possible, and help enable the internal use of open-source models with appropriate protections around inference, tool use, and data access.