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Anthropic· Technical Program Management · San Francisco, CA | Seattle, WA

Technical Program Manager, Inference Performance

Classified Tasks (21)

Automate 0%Augment 52%Human-Only 48%

Augment (11)

AI assists, human decides

Ensure reliability of inference systems across multiple hardware targets

technical

Partner with engineering teams to identify optimization opportunities in runtime and accelerator stacks

technical

Track performance metrics for inference systems and report progress against capacity and efficiency goals

analytical

Prioritize engineering work that unlocks capacity gains and efficiency improvements

leadership

Coordinate across runtime and accelerator layers to deliver performance improvements without compromising reliability

technical

Establish processes for cross-platform validation and verification of models and features

operational

Manage launch timelines and milestones for model and feature deployments

operational

Provide visibility into upcoming infrastructure changes and their organizational impact

communication

Translate technical complexities into clear updates for leadership and align stakeholders on priorities and timelines

communication

Identify inefficiencies in current workflows and drive systematic process improvements

analytical

Establish metrics and dashboards to track infrastructure health, capacity utilization, and deployment success rates

analytical

Human-Only (10)

Requires human judgment

Lead cross-functional initiatives for new infrastructure integration by establishing ownership, timelines, and communication channels between teams

leadership

Drive strategic initiatives across inference runtime and accelerator performance

leadership

Drive end-to-end planning for major infrastructure transitions, including platform modernization and new technology adoption

leadership

Coordinate model and feature launches across multiple hardware platforms to achieve end-to-end readiness

operational

Manage cross-platform dependencies between runtime, accelerator, and downstream teams

operational

Ensure smooth handoffs between runtime, accelerator, and downstream teams during launches

communication

Own and prioritize the inference deployment roadmap in collaboration with engineering leadership

leadership

Manage dependencies across teams and initiatives to keep deployment plans on schedule

operational

Build and maintain relationships across research, engineering, and product teams to capture requirements and constraints

communication

Remove blockers and coordinate resources to keep contended infrastructure teams delivering on schedule

operational

Job description

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Technical Program Manager for Inference, you'll be the critical bridge between our inference systems and the broader organization. You'll drive strategic initiatives across inference runtime and accelerator performance—coordinating model launches, managing cross-platform dependencies, and ensuring reliability across multiple hardware targets. This role is essential for keeping our most contended infrastructure teams shipping effectively while Research, Product, and Safety all depend on their output. Responsibilities: Systems Integration & Coordination : Lead cross-functional initiatives for new infrastructure integration, establishing clear ownership, timelines, and communication channels between teams. Drive end-to-end planning for major infrastructure transitions including platform modernization and new tech adoption. Performance & Efficiency: Partner with engineering teams to identify optimization opportunities, track performance metrics, and prioritize work that unlocks capacity gains. Coordinate across runtime and accelerator layers to ensure efficiency wins ship without compromising reliability. Launch Coordination: Drive end-to-end readiness for model and feature launches across multiple hardware platforms. Establish processes for cross-platform validation, manage launch timelines, and ensure smooth handoffs between runtime, accelerator, and downstream teams. Strategic Planning: Own and prioritize the inference deployment roadmap, working closely with engineering leadership to prioritize initiatives and manage dependencies. Provide visibility into upcoming changes and their organizational impact. Stakeholder Communication: Build strong relationships across research, engineering, and product teams to understand requirements and constraints. Translate technical complexities into clear updates for leadership and ensure alignment on priorities and timelines. Process Improvement: Identify inefficiencies in current workflows and drive systematic improvements. Establish metrics and dashboards to track infrastructure health, capacity utilization, and deployment success rates. You may be a good fit if you: Have several years of experience in technical program management, with proven success delivering complex infrastructure programs, preferably in ML/AI systems or large-scale distributed systems Have deep technical understanding of inference systems, compilers, or hardware accelerators to engage substantively with engineers and identify technical risks. Excel at creating structure and processes in ambiguous environments, bringing clarity to complex cross-team initiatives Have strong stakeholder management skills and can build trust with both technical and non-technical partners Are comfortable navigating competing priorities and using data to drive technical decisions Have experience with infrastructure scaling initiatives, hardware integrations, or deployment governance Thrive in fast-paced environments and can balance strategic planning with tactical execution Are passionate about AI infrastructure and understand the unique challenges of deploying and scaling large language models Deadline to apply: None, ap
Source: Anthropic careers · scraped 2026-05-22
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