Role Summary

You will lead a team of six engineers who build the data acquisition, post-processing, analytics and dashboarding tools our validation engineers depend on to rapidly turn vehicle test data into clear, defensible results. Our mission is simple: find the pain points in the validation engineering workflow and remove them, whether that means a new tool, an extension to an existing one, better automation, or teaching engineers a better practice.

This is a deliberately small, nimble team operating alongside much larger autonomy tooling and infrastructure organizations, and that shapes how we work. Our default is to leverage, customize and build on top of existing autonomy infrastructure and tooling whenever possible, instead of building parallel infrastructure of our own. You will bring the technical judgment behind those calls and will help drive the roadmap negotiations with peer organizations.

You will also help bring AI-powered tools and agents into how this team and its customers work - across test infrastructure, data pipelines, triage, and process automation, enabling a six-person team to deliver the impact of a much larger one.

Responsibilities

• Lead the team: Lead, coach and grow a team of six engineers, define the roadmap and prioritize the team's workflow against limited capacity, stay hands on and drive cross-functional technical alignment and process improvements.
• Own the charter: Data acquisition, post-processing, analytics, data tools test automation, fleet software integration, and in-house data loggers where production logging falls short.
• Partner before building: Serve as the primary interface to the larger Autonomy software, platform, and infrastructure organizations. Extend what they already own, and build only the thin, high-leverage layer closest to the validation engineer whenever possible versus building from scratch.
• Develop dashboards: Automated reporting for active safety and automated driving feature test results, regulatory scoring, vehicle operator safety and behavior metrics and increase throughput on release metrics and validation KPIs.
• Lead CI/CD and quality: Run the pipelines and automated test framework for the team's repositories, report release health and stability, hold the quality gates and metric traceability that make results defensible and demonstrate the team is accelerating validation.
• Apply AI to the workflow: Identify and deploy AI tools and agents for test data and log triage, prioritize critical validation scenarios, report drafting, and implement new targeted evaluation methodologies, with judgment about where agentic automation fits and when other methods are better suited.

Qualifications

• 5+ years in software engineering with a record of managing people and delivering cross-functional projects with a B.S. in Computer Science, Computer Engineering, Electrical Engineering, Robotics or related technical field.
• Strong hands-on Python experience building data tooling, pipelines, or analytics platforms for engineering or test organizations and demonstrated CI/CD and automated test framework experience (GitHub Actions, GitLab CI, or Jenkins, Docker, Pytest) in modern cloud services (AWS preferred).
• Practical experience with vehicle or robotics data: CAN (DBC, UDS / ISO 14229), automotive Ethernet, camera/radar/lidar logs, time synchronization, and formats such as MCAP, ROS, or MDF/MF4.
• Practical experience with LLMs and applied AI, including involvement with agent or automation systems and holding them to measurable accuracy metrics.
• Collaborative leader and clear communicator: Explain complex ideas simply, surface risks early, secure buy-in from stakeholders, develop meaningful dashboards and build a positive team culture.

Bonus Qualifications (0-4) Nice to have. .

• ADAS or autonomous vehicle validation and physical vehicle testing, including Euro NCAP, US NCAP, IIHS, ISO, or UN protocols and ISO 26262 / ISO 21448.
• Data logging hardware and embedded logging software, or test fleet software lifecycle: builds, configuration management, OTA updates, and data offload at scale.
• Exposure to autonomy simulation, resimulation, and log-replay tooling, and how simulated coverage complements physical vehicle test results.
• Complex, safety-critical, or fast paced, high-uptime environments, and stacks such as Grafana, Streamlit, Databricks, Snowflake, or Airflow.

Pay Disclosure

The salary range for this role is $186,000 - $232,500 for Palo Alto, California based applicants. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, geographic location, shift, and organizational needs.

The successful candidate may be eligible for annual performance bonus and equity awards.

We offer a comprehensive package of benefits for full-time and part-time employees, their spouse or domestic partner, and children up to age 26, including but not limited to paid vacation, paid sick leave, and a competitive portfolio of insurance benefits including life, medical, dental, vision, short-term disability insurance, and long-term disability insurance to eligible employees. You may also have the opportunity to participate in Rivian's 401(k) Plan and Employee Stock Purchase Program if you meet certain eligibility requirements. Full-time employee coverage is effective on their first day of employment. Part-time employee coverage is effective the first of the month following 90 days of employment. More information about benefits is available at rivianbenefits.com.

You can apply for this role through careers.rivian.com (or through internal-careers-rivian.icims.com if you are a current employee). There is no fixed deadline for this application; applications are accepted on an ongoing basis until the role is filled or the opening is no longer needed.