AI-Centric Release & Automation Software Engineer

General Motors; Sunnyvale (CA); On-site; USD 153,000 - 234,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Health Savings Account

Retirement savings plan

Paid vacation & holidays

Tuition assistance programs

GM vehicle discounts

Job summary

General Motors in Sunnyvale, CA is seeking an AI/Automation Release Engineer to accelerate AV software development through intelligent automation and AI-enabled workflows. You will collaborate with Release Engineers, Systems Engineers, DevOps, QA, and AI/ML teams to design automated release validation pipelines and integrate simulation with hardware-in-the-loop testing.

You will build engineering metrics, develop AI-enabled test analysis solutions, and establish governance for scalable

Qualifications

• Strong proficiency in Python and SQL; CI/CD experience with GitHub Actions, Jenkins, GitLab, or equivalent.
• Hands-on experience building ELT/ETL pipelines and integrating data from multiple sources.
• Experience applying AI/ML/LLM solutions to improve engineering productivity and testing workflows.
• Ability to evaluate AI outputs for accuracy, traceability, and usefulness in workflows.
• Strong analytical, debugging, and problem-solving skills across large-scale systems.
• Experience integrating simulation or hardware-in-the-loop testing into pipelines.
• Proven cross-functional collaboration across engineering, QA, and operations.
• Ability to learn quickly in a dynamic, high-stakes environment.
• Excellent communication to present data-driven insights to leadership.
• Bachelor’s, Master’s, or PhD in CS/EE/Robotics or equivalent experience.

Responsibilities

• Lead the design and implementation of automation across software development, testing, release, and operational workflows.
• Identify opportunities to apply AI, ML, and LLM-based tools to improve 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 that combine engineering, QA, simulation, test, and release information into actionable insights.
• Establish practical methods for evaluating accuracy, usefulness, traceability, and adoption of AI-enabled tools.
• Automate repetitive manual processes and measure improvements in cycle time, test efficiency, and 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 deliver effective automation solutions.
• Integrate tools such as Jira, GitHub, dashboards, observability platforms, and cloud services into unified workflows.
• Help define standards and governance for maintainable, secure, observable, and scalable automation and AI solutions.
• Communicate technical findings and measurable business impact to engineering and leadership.

Skills

Python

SQL

CI/CD

ETL/ELT pipelines

AI/ML

Data integration

Test automation

Release engineering

Education

Bachelor's/Master's/PhD in CS, EE, Robotics

Tools

Jira

GitHub

Grafana

Power BI

Job description

Job Description

You will be part of a core team that enables safe, reliable, and scalable releases of the Autonomous Vehicle (AV) software stack through intelligent automation, AI-enabled engineering workflows, and data-driven validation. The mission is to accelerate AV software development and release velocity by reducing manual effort, improving test and release visibility, and applying AI to engineering processes. In this position, you will collaborate closely with Release Engineers, Systems Engineers, DevOps, QA, 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-enabled solutions for test analysis, failure classification, defect triage, reporting, and workflow orchestration. You will help establish practical standards for evaluating, governing, and scaling automation and AI solutions while improving release readiness, software quality, and engineering productivity. If you are passionate about applying intelligent automation and systems thinking to accelerate the development of safe, high-quality ML-driven AV software, we want to talk to you.

What You’ll Be Doing

• 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 improve 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 that 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.

What You Must Have

• 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.

Bonus Points!

• Experience developing AI agents, copilots, retrieval-augmented generation systems, workflow automation, or intelligent engineering tools.
• Experience establishing governance, evaluation, monitoring, and security practices for AI-enabled engineering solutions.
• Knowledge of AV/ADAS software architectures, simulation validation loops, or automated vehicle testing.
• Experience with release governance, quality gates, or compliance processes for ML, AV, or safety-critical systems.
• Familiarity with reliability engineering concepts such as MTBF, FMEA, reliability growth analysis, and failure trend analysis.
• Experience building automation and metrics pipelines in AWS, GCP, Azure, or equivalent cloud environments.
• Familiarity with data visualization and observability tools such as Grafana, Superset, Power BI, or equivalent.
• Experience integrating Jira, GitHub Projects, or similar tools into automated release tracking, workflow orchestration, or engineering triage.
• Experience measuring automation impact through cycle-time reduction, defect prevention, reduced manual effort, improved test efficiency, or increased engineering throughput.

Compensation

The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

• The salary range for this role: is $153,200 to $234,100.
• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
• Benefits: GM offers a variety of health and wellbeing benefit programs.

Benefits

• Medical
• Dental
• Vision
• Health Savings Account
• Flexible Spending Accounts
• Retirement savings plan
• Sickness and accident benefits
• Life insurance
• Paid vacation & holidays
• Tuition assistance programs
• Employee assistance program
• GM vehicle discounts and more

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

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Our Company

Learn more about: Our Company Our Culture How we hire Our diverse team of employees bring their collective passion for engineering, technology and design to deliver on our vision of a world with Zero Crashes, Zero Emissions and Zero Congestion. We are looking for adventure-seekers and imaginative thought leaders to help us transform mobility.