Senior/Staff Technical Program Manager - Automation & Scaling

The Program Management Office (PMO) at Zoox is responsible for driving cross-functional program planning and execution at the highest level. We partner with leaders from across the company in vehicle development, system design, software engineering, manufacturing, fleet operations, and business functions to develop and deliver major corporate milestones on the path to launch, and beyond. Our program managers contribute to the end-to-end success of technical, integrated product milestones involving both of our vehicle platforms - the Toyota Highlander test fleet and Zoox's purpose-built robotaxi.

As Zoox scales its fleet and expands into new cities, we are evolving how we develop, validate, and release software by leveraging simulation, automation, faster triage, and scalable infrastructure. Our goal is to deliver improvements to our autonomous fleet faster and more frequently, while upholding our high bar for safety and quality.

As the Technical Program Manager for Automation & Scaling, you will own the systems that make that cadence possible. That means leveraging simulation to validate at scale, scaling the cloud infrastructure behind it, and automating the triage and metrics pipelines that shorten review cycles. This is a hands-on builder role. We are looking for a technically deep program leader who has built and deployed automation that measurably cut cycle time, and who can turn promising research and prototypes across Zoox into operational, production-grade systems.

Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent experience.

8+ years of experience in software engineering, technical program management, or a combination, with a strong software background.

A track record of designing and deploying automation that measurably reduced cycle time, such as CI/CD, test, data, or triage pipelines.

Hands-on familiarity with AWS and large-scale distributed compute and data systems, including simulation workloads.

Experience building or applying AI/ML-based tools to analyze logs, detect failures, or automate engineering workflows.

Proven ability to take research or prototype work into production, and to influence technical experts without formal authority.

Excellent written and verbal communication, including turning technical bottlenecks into clear decisions for leadership.

Deep experience leveraging simulation platforms, virtual validation strategies, or synthetic data in autonomous vehicles or robotics.

Experience moving a large engineering organization from infrequent releases to a release train or continuous delivery model.

Experience with release qualification, verification and validation, or safety-critical software.

Hands-on coding experience in Python or similar, building internal tools and automation.