Engineering Manager, Agent Runtime Platform

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 The Agent Runtime Platform provisions and runs the compute and runtimes behind Anthropic's internal agents: secure, credential-managed environments where agents do real engineering and knowledge work at scale. As an Engineering Manager on these teams, you will be responsible for ensuring you and your team are identifying and removing friction and blockers to productivity, experimenting at the frontier, and building security and quality into agents. You also will help bring clarity, focus, and context to your teams in a fast-paced, dynamic environment. Responsibilities · Own the technical strategy and roadmap, translating goals into concrete execution · Manage day-to-day execution of the team's work · Prioritize the team’s work and manage projects in a highly dynamic, fast-paced environment · Stay hands-on: build and ship the runtime platform and tooling · Define what secure agent execution means at scale, partnering with security teams on sandboxing, isolation, and credential management · Build primitives that are composable and reusable across various agents · Own infrastructure scalability and reliability: capacity planning across cloud providers, right-sizing, and operational excellence · Collaborate cross-team, supporting internal teams bringing up their agents You May Be a Good Fit If You: · Have 10+ years building and operating large-scale platforms or distributed systems · Have 1+ years of management experience in a technical environment, particularly in building platforms or agents at scale · Are deeply interested in the potential transformative effects of advanced AI systems and agents, and are committed to ensuring their safe deployment · Have experience with container or VM orchestration at scale · Are obsessed with productivity and transforming how we work · Have excellent communication skills and enjoy supporting internal partners Strong Candidates May Also Have: · Engineering management experience on top of a strong IC track record · Experience with harness engineering · Experience with building security-sensitive infrastructure: sandboxing, workload isolation, credential management, or access control · Experience with capacity planning and utilization across multiple cloud providers · Experience working with researchers, engineers and other functional roles 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.