Technical Program Manager, Cloud Inference

Anthropic Anthropic · AI Frontier · San Francisco, CA · Technical Program Management

This role is for a Technical Program Manager focused on cloud inference deployments for AI models. The TPM will coordinate engineering efforts internally and with major cloud partners (Amazon Bedrock, Google Vertex, Microsoft Foundry) to ensure efficient product development and launch pipelines for AI models on these platforms. Responsibilities include defining and scoping technical initiatives, owning launch readiness, acting as the primary technical interface to cloud partners, driving cross-functional alignment, and reporting on program status.

What you'd actually do

  1. Partner with engineering leaders to define, scope, and sequence major technical initiatives for cloud partnerships and AI model deployment, and own the plans, timelines, and resourcing to land them.
  2. Own launch readiness for Claude models on partner cloud platforms: checklist, blocker tracking, joint go/no-go with the partner, and post-launch stability follow-through.
  3. Act as the primary technical interface to cloud partner engineering orgs — owning the relationship, the shared roadmap, and day-to-day coordination on deployment, capacity, and incidents.
  4. Drive cross-functional alignment across internal engineering, product, and go-to-market teams to land joint deliverables with the partner.
  5. Provide clear and transparent reporting on program status, issues, and risks to executives and stakeholders.

Skills

Required

  • technical program management
  • delivering complex technical programs
  • cloud platforms
  • AI technologies
  • cloud computing architectures
  • AI/ML deployment
  • integration challenges
  • interpersonal and communication skills
  • influence without authority
  • cross-organizational support
  • navigating ambiguity
  • strategic priorities
  • rapid, high-quality execution
  • fast-paced, scaling environments
  • bring order to chaos

Nice to have

  • hyperscaler's managed AI platform (Amazon Bedrock, Google Vertex AI, or Azure AI Foundry)
  • ML inference
  • model serving infrastructure
  • accelerator-based compute
  • release engineering
  • deployment automation
  • CI/CD

What the JD emphasized

  • cloud partner engineering orgs
  • joint engineering roadmap
  • dependency tracking
  • incident follow-through
  • converting open issues into a prioritized plan both sides commit to