Engineering Manager, Continuous Deployment and Change Safety (AI)

TL;DR

Engineering Manager, Continuous Deployment and Change Safety (AI): Leading the development of continuous-deployment, configuration, and feature-flagging platforms with an accent on deployment safety and reliability. Focus on building progressive rollout systems, automating health checks, and establishing the golden path for safe deployments across the engineering organization.

Location: Hybrid (San Francisco, CA or New York City, NY). Must be in office at least 25% of the time

Salary: $405,000 - $485,000 USD per year

Company

Anthropic is a public benefit corporation dedicated to creating reliable, interpretable, and steerable AI systems that are safe and beneficial for society.

What you will do

• Lead and grow a team of engineers building continuous-deployment, configuration, and feature-flagging platforms.
• Set the technical direction for the safe deployment of code, infrastructure, and configuration.
• Partner with product, inference, security, and infrastructure teams to standardize the "paved path" for deployments.
• Drive the roadmap for progressive rollouts, health-check automation, and expansion to new deployment surfaces.
• Define and track metrics for deployment safety and speed to hold the team accountable.
• Manage hiring, coaching, and career development to sustain a high-performing, healthy team.

Requirements

• Experience managing and growing teams of software engineers.
• Hands-on software engineering background as an individual contributor.
• Experience building or operating backend, distributed, or infrastructure systems in production.
• Working knowledge of CI/CD pipelines, Kubernetes, and infrastructure-as-code.
• Excellent written and verbal communication skills.
• Must be based in or able to work from San Francisco, CA or New York City, NY.

Nice to have

• 5+ years of engineering management experience leading platform or developer-experience teams.
• Experience with release engineering, canary, or blue-green deployments and automated rollbacks.
• Experience with feature flagging or experimentation platforms.
• Background in observability, health checking, or incident response.
• Experience treating configuration as a first-class, safely deployed artifact.

Culture & Benefits

• Collaborative "big science" approach to AI research.
• Competitive compensation and optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours and high-quality office spaces for collaboration.
• Visa sponsorship availability.