Engineering Manager, Agent & Product Security Engineering · · New York; San Francisco Apply →

Cursor; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Cursor in New York seeks an Engineering Manager for Agent & Product Security to lead a team focused on trustworthy agentic software development. You’ll define security primitives such as identity, delegated authority, policy enforcement, secure tool execution, and containment across Cursor’s products and agents.

You’ll hire and coach a high‑performing security engineering team while staying technically close to the work and collaborating with product, infrastructure, ML, and customer teams to

Qualifications

• Led engineering teams shipping production systems with high security, reliability, or platform stakes.
• Strong product and systems judgment: reason from user workflows to architecture, threat models, enforcement points, and tradeoffs.
• Understanding of modern application security, authorization, tenancy, identity, secrets, data isolation, and secure-by-default platform design.
• Good instincts about AI agents: tool usage, authority sources, prompt injection and exfiltration mitigations.

Responsibilities

• Chart the path from supervised agents to trusted autonomous ones and define security primitives for agent autonomy.
• Engineer the isolation that makes Cursor safe to run inside customers’ codebases: tenancy, workspace, secret, and data protections.
• Build the authority infrastructure autonomous agents need: identity, scoped permissions, policy enforcement, and secure tool execution.
• Build customer-facing security controls with clear success metrics for security outcomes.
• Hire, coach, and grow a high-performing security engineering team while staying technically close to the work.

Job description

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.

SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

About the role

Cursor’s agents work inside the codebases of some of the most security-conscious engineering organizations in the world — holding credentials, reading untrusted content, running tools, and shipping changes. Today they act on authority delegated per task. Where we’re headed, they’ll work more like coworkers: autonomous over long horizons, holding standing responsibilities, initiating work, and collaborating with people and other agents. The security models that future needs — identity and accountability for autonomous workers, standing authority rather than per-task permission, agent-to-agent trust, oversight that scales with always-on autonomy — mostly don’t exist yet.

As Engineering Manager for Agent & Product Security, you’ll lead the team that makes agentic software development trustworthy. This team owns the security boundaries between customers, data, tools, repositories, workspaces, and agent authority across Cursor’s product and agents and designs the primitives behind them: agent identity, delegated authority, policy enforcement, secure tool execution, and prompt-injection containment. Little of this has settled precedent, so the team’s decisions carry unusual weight for Cursor and for how the industry approaches these problems.

Security here is tightly coupled to product strategy: customers adopt agent autonomy as fast as we can make it trustworthy, so the boundaries your team makes safe directly determine what the product can ship. You’ll help set that direction.

What you’ll do

Chart the path from supervised agents to trusted autonomous ones: define the security primitives that enable agent autonomy, and lead the team that builds them.

Engineer the isolation that makes Cursor safe to run inside customers’ most valuable codebases: tenancy, workspace, secret, and data protections designed for real adversaries.

Build the authority infrastructure autonomous agents need: identity, scoped permissions, policy enforcement, and secure tool execution, so an agent can hold real responsibility with verifiable limits and full accountability.

Build customer-facing security controls that are understandable, usable, and strong enough for Cursor’s most security-sensitive customers, with crisp success metrics for security outcomes.

Hire, coach, and grow a high-performing security engineering team while staying technically close to the work: write and review code where useful, and keep execution fast and technically grounded.

You may be a fit if

You’ve led engineering teams shipping production systems with high security, reliability, or platform stakes — and you want a problem space where much of the answer isn’t written down yet.

You have strong product and systems judgment: you can reason from user workflows to architecture, threat models, enforcement points, and operational tradeoffs — and you see security as something that enables product capability, not only restricts it.

You understand modern application security, authorization, tenancy, identity, secrets, data isolation, and secure-by-default platform design.

You have good instincts about AI agents: how they use tools, where authority should come from, how prompt injection and exfiltration show up in practice, and how to build mitigations that hold up against creative adversaries.

You’re comfortable operating in ambiguity: you can set strategy where precedent is thin, commit to a direction, and stay close enough to the implementation to know when to change it.

You can partner well across product, infrastructure, ML, and customer-facing teams.

#LI-DNI

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