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Engineering Manager, Continuous Deployment and Change Safety

Anthropic
CompanyAnthropic
CategoryEngineering
LocationSan Francisco
RemoteOn-site (inferred)
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted8 Jul 2026
Last verified2 Aug 2026
SourceEmployer ATS (greenhouse)
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Description
About Anthropic 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 Anthropic's services change constantly. Application code, infrastructure, and runtime configuration all move to production many times a day. Our Safe Change team builds the continuous-deployment and feature-flagging systems that make those changes safe and reliable. The continuous-deployment platform moves a change through staged promotion, runs health checks at each phase of deployment, and gives service owners the levers to respond the moment something regresses. We provide the tools to modify runtime behavior, roll out configuration safely, and test changes. This team provides the paved path that lets everyone at Anthropic ship frequently without trading away reliability or security. We're looking for an engineering manager to lead this team. The continuous-deployment platform is already widely adopted across Anthropic, and the mandate is expanding quickly: bringing configuration changes onto the same safe path as code, supporting additional deployment surfaces, building progressive rollouts, and establishing the golden path for safe deployments that every team across the company will rely on. You'll lead a team building infrastructure that nearly every other engineer at Anthropic depends on, and you'll partner closely with product, inference, security, and infrastructure teams to make deployment safety a standard property of the platform rather than something each team reinvents. Key responsibilities Lead and grow a team of engineers building Anthropic's continuous-deployment, configuration, and feature-flagging platforms, owning planning, execution, and delivery against key milestones Set technical direction for the safe deployment of code, infrastructure, and configuration across Anthropic's services Partner with product, inference, security, and infrastructure teams to migrate services onto the paved path and make safe deployment the default Drive the roadmap for progressive rollouts, health-check automation, first-class configuration deployment, and expansion to new deployment surfaces Define and track the metrics that measure deployment safety and speed and hold the team accountable to them Create clarity for the team and stakeholders in an ambiguous, fast-moving environment where the platform is still being built out Take an inclusive, equitable approach to hiring, coaching, and career development, and sustain a high-performing, healthy team Represent the team across the engineering organization and contribute to engineering-wide initiatives as a member of Anthropic's engineering management group Minimum qualifications Experience managing and growing a team of software engineers A hands-on software engineering background as an individual contributor prior to moving into management Experience building or operating backend, distributed, or infrastructure systems in production Working knowledge of modern deployment and cloud-native tooling, such as CI/CD pipelines, Kubernetes, and infrastructure-as-code Excellent written and verbal communication skills, including the ability to create clarity across teams Preferred qualifications 5+ years of engineering management experience, including leading infrastructure, platform, or developer-experience teams Experience owning continuous delivery, release engineering, or deployment-safety systems Familiarity with progressive delivery techniques such as canary or blue-green deployments and automated rollback Experience with feature flagging or experimentation platforms A background in observabilit
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