Technical Product Manager, Data Infrastructure

About the Role

We are looking for a Technical Product Manager, Data Infrastructure to own strategic customer data deliveries and help build Lightwheel’s Data Delivery Platform into scalable, reusable infrastructure.

Responsibilities

• Own Data Platform — Define and evolve data schemas, validation, adapters, conversion, cloud transfer, APIs/SDKs, observability, and cost optimization.

• Drive Customer Delivery — Translate customer requirements into technical specifications, acceptance criteria, and delivery plans; own programs end-to-end through customer acceptance.

• Scale Data Operations — Build systems and processes capable of supporting 100K–1M+ data-hour programs with predictable throughput, reliability, and cost.

• Solve Complex Technical Problems — Identify and resolve bottlenecks across compute, storage, networking, data pipelines, APIs, and customer ingestion.

• Build Scalable Processes — Standardize delivery workflows, quality gates, versioning, and change management to make customer onboarding repeatable and scalable.

• Lead Cross-Functional Execution — Work closely with Engineering, Data Operations, Infrastructure, and customers to drive technical delivery and continuously improve the platform.

Qualifications

• 3+ years of experience in software engineering, data infrastructure, distributed systems, ML/robotics infrastructure, or customer engineering.

• Strong hands-on engineering background with Python, APIs/SDKs, AWS/GCP, Kubernetes, and data pipelines.

• Experience building or operating production data platforms or large-scale data pipelines.

• Strong problem-solving skills with the ability to diagnose bottlenecks across compute, storage, network, and APIs.

• Experience working directly with technical customers and leading cross-functional projects.

• Fluent in English and Mandarin.

Preferred Qualifications

• Experience in robotics, autonomous driving, embodied AI, or Physical AI.

• Experience with large-scale video, sensor, multimodal, or ML training datasets.

• Familiarity with LeRobot, MCAP, ROS bags, TB/PB-scale data, or cloud data transfer.

• Experience in forward-deployed engineering, enterprise data integration, or building infrastructure functions from the ground up.