Engineering Manager, Cybersecurity Products

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. 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. This is a builder's role. The team is small, the pace is high, and you should expect to be in the code, in customer calls, and in research reviews the same week. You also need to scale the team without losing the prototyping energy that got the product here. 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 You may be a good fit if you · Have 8+ years of software engineering experience and 4+ years managing engineers, with ownership of a team's hiring, performance, and technical direction · Have shipped cybersecurity products in production (SIEM, EDR, vulnerability management, application security, threat detection, incident response, or security automation) · Have taken a team from prototype through first paying customers to scaled deployment · Are technical and hands-on: comfortable in design reviews and in the team's code · Have 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 · Treat direct customer contact as a primary input to your roadmap Strong candidates may also 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 For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000—$485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.