Technical Program Manager, AI Infrastructure
Leads high-impact AI infrastructure programs for model training, evaluation, and serving at scale. Partners with engineering, research, and product teams to align roadmaps, drive execution, track metrics, and optimize workflows in technically complex environments. Requires 5-8 years experience in technical program management.
About the job
What You’ll Do
- Lead planning and execution of major AI infrastructure initiatives spanning training pipelines, data systems, model evaluation, and inference/serving
- Build structures that keep teams aligned: scopes, goals, requirements, timelines, risks, and success metrics
- Partner with engineering, research, and product to translate model and product needs into infrastructure roadmaps and priorities
- Drive cross-functional accountability and communication across teams working on tightly coupled systems
- Track key infrastructure metrics (e.g., reliability, latency, throughput, cost efficiency) and define reporting that surfaces progress and risk
- Identify bottlenecks in infrastructure workflows and lead efforts to improve tooling, automation, and developer velocity
- Support capacity planning and resource allocation to ensure infrastructure scales with model and product growth
- Develop repeatable frameworks and operational patterns that improve execution quality across infrastructure programs
- Serve as a strategic partner to leaders on prioritization, sequencing, and tradeoffs across infrastructure investments
- Work closely with AI cloud providers and serve as the primary bridge between internal engineering teams and external partnership efforts
- Technical understanding of GPU clusters, AI accelerator chips, and cloud providers to effectively evaluate requirements and guide infrastructure decisions
What You’ll Bring
- 5–8 years of experience in program management, technical operations, or product execution in a fast-moving, technical environment
- Proven ability to lead complex, multi-team initiatives spanning engineering and infrastructure systems
- Strong communication skills with the ability to bridge technical and non-technical stakeholders
- Experience working closely with engineering teams on distributed systems, cloud infrastructure, or platform development
- Ability to break down ambiguous problem spaces into clear plans and drive alignment across teams
- Analytical mindset with experience using data to inform decisions and measure impact
- Strong ownership and execution mindset, with the ability to manage multiple priorities simultaneously
Skills
Gpu Clusters, Ai Accelerator Chips, Cloud Providers, Distributed Systems, Cloud Infrastructure, Platform Development, Training Pipelines, Data Systems, Model Evaluation, Inference/Serving
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