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Anthropic is seeking an engineering manager in New York to lead the Safe Change team’s continuous-deployment, configuration, and feature-flagging platforms. You’ll guide a growing group of engineers and work with product, inference, security, and infrastructure teams to scale a safe, reliable deployment path across Anthropic’s services.
You will set technical direction for deployment safety, drive progressive rollouts, and establish standard practices while mentoring team成员 and advancing a
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.
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.
$405,000 — $485,000 USD
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
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.