Technical Program Manager, Databases

USD 365,000-435,000 per year
MIDDLE
✅ Hybrid
✅ Visa Sponsorship

Used Tools & Technologies

Not specified

Required Skills & Competences

Communication @ 3 API @ 3 AI @ 3

Details

Anthropic’s databases underpin every service the company runs: Claude, our APIs, and the internal systems behind them. This Technical Program Manager role drives the strategy and execution to take Anthropic's database infrastructure to the next level of availability and scale. The role focuses on three interlocking strategies: cross-region resilience and locality, multi-cloud operation across hyperscalers, and deployments spanning private, public, and hybrid cloud environments. Success means a highly available, 24x7x365 database infrastructure that all Anthropic services can depend on.

Responsibilities

  • Own the roadmap and execution across the three strategy pillars, turning architectural direction into sequenced, deliverable programs
  • Coordinate across a broad set of partners: database vendors, hyperscalers, internal platform teams, and infrastructure teams
  • Manage external vendor and hyperscaler relationships at the working level, including commitments, escalations, and joint roadmaps
  • Drive dependencies, risks, and tradeoffs associated with operating databases as critical infrastructure
  • Create program documentation including roadmaps, status reports, risk assessments, and communication plans
  • Facilitate technical decision-making by bringing together stakeholders, driving consensus, and ensuring timely resolution of blocking issues

Requirements

  • Several years of experience in technical program management with a track record of delivering complex, cross-functional programs
  • Experience with database, storage, or core infrastructure programs and the ability to engage meaningfully with engineers who design and operate them
  • Experience managing external vendor or cloud provider relationships at the working level (commitments, escalations, joint roadmaps)
  • Experience with cross-region, multi-cloud, or hybrid cloud infrastructure is preferred
  • Highly organized with the ability to manage multiple parallel workstreams across distributed teams
  • Able to thrive in unstructured environments and bring clarity in ambiguous situations
  • Excellent written and verbal communication skills and the ability to influence without authority
  • Passion for Anthropic's mission and interest in operating AI infrastructure safely and reliably

Compensation

  • Annual Salary: $365,000 - $435,000 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: will correlate with the internal job level requirements for the position
  • Location-based hybrid policy: staff are expected to be in one of Anthropic's offices at least 25% of the time; some roles may require more time in office
  • Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to assist; sponsorship is not guaranteed for every role/candidate

Benefits

  • Competitive compensation and benefits
  • Optional equity donation matching
  • Generous vacation and parental leave
  • Flexible working hours
  • Office space for collaboration

About Anthropic

Anthropic is a public benefit corporation headquartered in San Francisco. The company's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The team includes researchers, engineers, policy experts, and business leaders working on large-scale research efforts and frequent collaborative research discussions.

How we're different

Anthropic focuses on a few large-scale research efforts, values impact over smaller puzzles, and treats AI research as an empirical science. The company emphasizes collaboration, communication skills, and working on high-impact directions such as interpretability, scaling laws, and learning from human preferences.