Technical Program Manager, Cloud Inference at Anthropic

Hybrid - San Francisco, CA, USA

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We are seeking an experienced Technical Program Manager to support our critical cloud deployments. In this role you will be an execution owner, driving coordination and collaboration across multiple engineering teams and our major cloud partners, ensuring tight coordination on engineering deliverables and enabling repeatable and efficient product development and launch pipelines for our AI models on third‑party platforms.

Salary

USD 290,000 - 435,000

Requirements

Skills

  • Have several years of experience in technical program management, with a track record of successfully delivering complex technical programs, preferably involving cloud platforms and AI technologies.
  • Have strong understanding of cloud computing architectures, AI/ML deployment, and integration challenges.
  • Have exceptional interpersonal and communication skills, enabling you to influence without authority and build cross‑organizational support.
  • Have a high threshold for navigating ambiguity and ability to balance strategic priorities with rapid, high‑quality execution.
  • Thrive in fast‑paced, scaling environments with the ability to bring order to chaos.
  • Are passionate about Anthropic's mission and committed to ensuring AI is developed safely.
  • Direct experience with a hyperscaler's managed AI platform — Amazon Bedrock, Google Vertex AI, or Azure AI Foundry — including how partners list, launch, and onboard customers on it.
  • Background in ML inference, model serving infrastructure, or accelerator‑based compute.
  • Have owned joint engineering roadmap or dependency tracking, driving incident follow‑through, and converting open issues into a prioritized plan both sides commit to.
  • Experience with release engineering, deployment automation, or CI/CD for systems that ship to multiple targets or environments.

Responsibilities

  • 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.
  • 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.
  • 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.
  • Drive cross‑functional alignment across internal engineering, product, and go‑to‑market teams to land joint deliverables with the partner.
  • Provide clear and transparent reporting on program status, issues, and risks to executives and stakeholders.

Technologies

Amazon BedrockGoogle Vertex AIMicrosoft FoundryAzure AI FoundryCloud computing architecturesAI/ML deploymentIntegration challengesRelease engineeringDeployment automationCI/CDML inferenceModel serving infrastructureAccelerator-based compute

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