Anysphere은 에이전트 기반 소프트웨어 개발의 신뢰성을 확보할 Engineering Manager를 채용합니다. 보안 엔지니어링 팀을 리드하며 에이전트의 자율성, 권한 관리, 데이터 격리 등 핵심 보안 아키텍처를 설계합니다. 프로덕션 시스템 운영 경험과 AI 에이전트 보안에 대한 깊은 이해가 필수입니다. 모호한 환경에서 전략을 수립하고 기술적 실행력을 발휘할 리더를 찾습니다.
Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.
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.
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’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.
