Engineering Manager, Cybersecurity Products

About the role

We are hiring an Engineering Manager to lead a team of engineers building AI-powered cybersecurity products. The work spans research, product, and go-to-market. Your team will prototype and ship products that use frontier models to defend code and infrastructure. You will set technical direction, partner with research to turn new model capabilities into products, and stay close to customers so the team builds the right things, not just builds things well.

Responsibilities

• Lead and grow the team: hiring, performance, and the culture that keeps strong engineers doing their best work
• Stay close to customers, design partners, and the security community; turn what you learn into products and unblock the team on the ones that matter
• Own architectural decisions across the full stack, from agentic systems and model orchestration to product surfaces, integrations, and data infrastructure
• Coordinate with GTM, partnerships, and other product areas
• Grow the next layer of leadership on the team

Requirements

• 8+ years of software engineering experience and 4+ years managing engineers, with ownership of a team's hiring, performance, and technical direction
• Shipped cybersecurity products in production (SIEM, EDR, vulnerability management, application security, threat detection, incident response, or security automation)
• Taken a team from prototype through first paying customers to scaled deployment
• Technical and hands-on: comfortable in design reviews and in the team's code
• Strong product instincts and a record of helping teams decide what to build, not just how
• Communicate clearly across functions and keep research, product, GTM, and executive partners aligned through ambiguity
• Care deeply about Anthropic's mission and about developing AI responsibly and safely

Qualifications

• May have experience with hands-on security expertise: application security, vulnerability research, reverse engineering, incident response, penetration testing, or detection engineering
• Building products on LLMs, including agentic systems, evals, and prompt and model iteration loops
• Strict data-handling environments (BYOC, CMEK, regulated industries, governments)
• Both startup and enterprise-scale company experience
• Working closely with research to translate capability into shipped product
• Ecosystem partnerships and MCP, CI/CD, or source-control integrations