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Aurora

Robot type
Autonomous Vehicle
Location
DallasTexasUSA
Job type
Hardware
Posted
Aug 3, 2026
Salary
$178,000–$285,000 a year
Full-time

Senior Manager Hardware Systems Applications Engineering

Job description

Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.

Job responsibilities

  • Work on-site in the DFW area which is our center of excellence for fleet operations.
  • Synthesize top-level business goals with the team charter to plan quarterly goals for the team and work with the team to track and drive them to completion
  • Define key inputs and outputs for the team, and develop internal to team processes to ensure consistent execution of the team’s deliverables.
  • Define staffing needs for the team and manage resource planning of the existing team to meet business needs (Eg shift scheduling, training needs identification etc)
  • Develop and manage cross-functional workflows between software, product, operations and other HW engineering teams to ensure clear handoff on deliverables.
  • Develop, maintain and track metrics that provide real-time signal on hardware health and performance
  • Communicate upward to leadership with respect to team deliverables, ranging from top-level fleet metrics to low-level details on specific issue investigations on a weekly basis.
  • Travel up to 30% from the “home office” to one of: Engineering sites (PIT, MTV), Operations sites (PAL, FTW, El Paso, PHX, HOU) and Remote test locations (TRC Ohio)

Job requirements

  • BS in Engineering
  • 10+ years managing direct reports including remote / offsite personnel
  • 10+ years experience developing RASICs, process definitions, workflow definitions with cross-functional teams.
  • 10+ years of work-related experience in the Automotive Engineering field, specifically with sustaining engineering of fielded products.
  • Expertise using JIRA for issue management, including creation of custom reports, dashboards etc and driving continuous improvements on existing workflows.
  • Ability to be objective (data-driven) and apply an empirical process to solving issues.
  • Hands-on experience using AI tools and agents to expedite workflow execution.
  • Hands-on experience using data analytics platforms like Mode, Holistics or similar to develop data driven metrics of success at an enterprise level.

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