Senior AI-Centric Release & Automation Software Engineer
$153k - $234k • Sunnyvale, California, United States of America • Full-time
Posted 1mo ago
About the job
You will join a core team focused on enabling safe, reliable, and scalable releases of Autonomous Vehicle (AV) software through intelligent automation and AI-enabled engineering workflows. The goal is to accelerate AV software development and release velocity by minimizing manual effort, enhancing test and release visibility, and applying AI to engineering processes. You will collaborate with various engineering and AI/ML teams to design and implement automated release validation pipelines, integrate simulation and hardware-in-loop testing, build engineering metrics, and develop AI solutions for tasks like test analysis, failure classification, defect triage, and workflow orchestration. This role involves establishing practical standards for evaluating, governing, and scaling automation and AI solutions to improve release readiness, software quality, and engineering productivity.
Responsibilities
- Lead the design and implementation of automation across software development, testing, release, and operational workflows.
- Identify opportunities to apply AI, machine learning, and LLM-based tools to enhance engineering productivity and decision-making.
- Build AI-enabled solutions for test analysis, failure classification, defect triage, documentation, reporting, and workflow orchestration.
- Develop and maintain scalable CI/CD integrations supporting simulation, hardware-in-loop, regression, and release validation activities.
- Build data pipelines to combine engineering, QA, simulation, test, and release information into actionable insights.
- Establish practical methods for evaluating the accuracy, usefulness, traceability, and adoption of AI-enabled engineering tools.
- Automate repetitive manual processes and measure improvements in cycle time, test efficiency, defect prevention, and engineering throughput.
- Improve visibility into test health, regression trends, flaky tests, failure patterns, and release readiness.
- Collaborate with engineering, QA, operations, data, and program teams to understand pain points and deliver effective automation solutions.
- Integrate tools such as Jira, GitHub, dashboards, observability platforms, and cloud services into unified engineering workflows.
- Help define standards and governance for maintainable, secure, observable, and scalable automation and AI solutions.
- Communicate technical findings, process improvements, and measurable business impact to engineering and leadership stakeholders.
Requirements
- Strong proficiency in Python and SQL.
- Proven experience in CI/CD systems (e.g., GitHub Actions, Jenkins, GitLab, or equivalent).
- Hands-on experience developing ELT/ETL pipelines and integrating data from engineering, QA, simulation, and operational systems.
- Experience applying AI, machine learning, or LLM-based solutions to improve engineering productivity, test analysis, defect triage, documentation, or decision-making.
- Ability to evaluate AI-generated outputs for accuracy, consistency, traceability, and usefulness in engineering workflows.
- Strong analytical, debugging, and problem-solving skills across large-scale software systems.
- Experience integrating simulation or hardware-in-loop testing into automated pipelines.
- Track record of cross-functional collaboration across engineering, QA, and operations teams.
- Ability to learn quickly and operate effectively in a dynamic, high-stakes environment.
- Excellent communication skills for presenting data-driven insights to engineering and leadership stakeholders.
- Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field—or equivalent experience.
Benefits
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.