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