Technical Program Manager, Cloud Inference

About the role

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. You will also support the collaboration and technical execution between our internal engineering teams and our major cloud partners including Amazon Bedrock, Google Vertex, and Microsoft Foundry.

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.

Qualifications

• 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.
• Be passionate about Anthropic's mission and committed to ensuring AI is developed safely.

Benefits

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $290,000 - $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: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy

We currently 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.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

Our research directions

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

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