Own end-to-end delivery of the engineering tools portfolio: data pipelines, visualization and comparison tools, optimization workflows, and AI agentic workflows used across the motor organization
Drive daily execution – scope, timelines, dependencies, and blockers – with direct, hands-on follow-up rather than second-hand status
Establish single-threaded ownership for every active workstream, so each project has one clearly accountable engineer
Define and enforce the quality bar: architecture reviews, code review standards, testing, documentation, and performance expectations for high-volume engineering datasets
Break ambiguous engineering needs into well-scoped, estimable work, and push back on scope that does not earn its cost
Identify and remove bottlenecks, both technical (infrastructure, data access, tooling, CI) and organizational (unclear requirements, cross-team dependencies)
Partner with motor designers, test engineers, and software developers to translate engineering needs into a prioritized, realistic roadmap
Drive adoption of AI coding agents across the team to increase throughput – while insisting that engineers review and own every choice those agents make
Report clearly to leadership on progress, risk, and trade-offs, with no surprise

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