About the job
About the Role
Character. AI is hiring a Technical Program Manager for the AI Infrastructure team in Redwood City, CA. This position focuses on leading large-scale programs that strengthen model development and serving systems. The role involves close collaboration with engineering, research, and product teams to shape infrastructure strategies, coordinate project plans, and deliver on important initiatives related to training, evaluation, and inference. The work supports rapid iteration and helps improve AI experiences for millions of users.
This position suits someone who thrives in technically complex settings, enjoys bringing structure to ambiguous problems, and can build consensus across cross-functional teams. The work often sits at the intersection of research and production, requiring thoughtful navigation of trade-offs between speed, quality, and reliability. Success depends on influencing without formal authority, spotting risks early, and keeping momentum on broad, interconnected projects.
Key Responsibilities
- Lead the planning and delivery of major AI infrastructure projects, covering training pipelines, data systems, model evaluation, and inference or serving workflows.
- Set up frameworks that keep teams aligned on scope, objectives, requirements, timelines, risks, and success metrics.
- Work with engineering, research, and product groups to turn model and product needs into clear infrastructure roadmaps and priorities.
- Encourage accountability and clear communication among teams handling related systems.
- Track key infrastructure metrics such as reliability, latency, throughput, and cost efficiency, and prepare reports highlighting progress and potential risks.
- Find and address bottlenecks in infrastructure workflows, improving tooling, automation, and developer productivity.
- Support capacity planning and resource management to ensure infrastructure scales with model and product growth.
- Develop scalable frameworks and operational practices to raise the quality of execution across infrastructure projects.
- Advise leadership on prioritization, sequencing, and trade-offs in infrastructure investments.
- Engage with AI cloud service providers and act as the primary point of contact between internal engineering teams and external partners.

