Senior AI-Centric Release & Automation Software Engineer

General Motors; Sunnyvale (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

General Motors in Sunnyvale, CA is seeking a highly skilled automation and AI-enabled engineering specialist to advance the AV software release pipeline. You will design automated release validation, integrate simulations, and create data-driven metrics to speed development while maintaining safety and quality.

You will collaborate with Release Engineers, Systems Engineers, DevOps, QA, and AI/ML teams to implement pipelines, apply AI to testing and triage, and improve cycle time and release

Qualifications

• Strong proficiency in Python and SQL.
• Experience in CI/CD systems (GitHub Actions, Jenkins, GitLab).
• Hands-on experience with ELT/ETL pipelines and data integration from multiple systems.
• Experience applying AI/ML/LLM solutions to engineering productivity, testing, or decision-making.
• Ability to evaluate AI outputs for accuracy and usefulness.
• Proven analytical, debugging, and problem-solving skills.
• Experience integrating simulation or hardware-in-loop testing into automated pipelines.
• Track record of cross-functional collaboration across engineering, QA, and operations.
• Bachelor's, Master's, or PhD in CS/EE/Robotics or related field (or equivalent).

Responsibilities

• Lead design and implementation of automation across development, testing, release, and operations workflows.
• Identify opportunities to apply AI/ML/LLM tools to improve productivity and decision-making.
• Build AI-enabled solutions for test analysis, failure classification, defect triage, documentation, reporting, and orchestration.
• Develop and maintain scalable CI/CD integrations supporting simulation, hardware-in-loop, regression, and release validation.
• Create data pipelines combining engineering, QA, simulation, test, and release data into insights.
• Establish methods to evaluate the accuracy and adoption of AI-enabled tools.
• Automate repetitive processes and measure improvements in cycle time, test efficiency, and defect prevention.
• Improve visibility into test health, regression trends, flaky tests, and release readiness.
• Collaborate with engineering, QA, operations, data, and program teams to deliver automation solutions.
• Integrate Jira, GitHub, dashboards, observability platforms, and cloud services into workflows.
• Define governance for scalable, secure, observable automation and AI solutions.
• Communicate findings and measurable business impact to engineering and leadership stakeholders.

Skills

Python

SQL

Analytical thinking

Communication skills

Problem solving

Cross-functional collaboration

Learning quickly

Education

Bachelor's/Master's/PhD in CS, EE, Robotics, or related field

Tools

GitHub Actions

Jenkins

GitLab

Job description

Job Description

The Role

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 velo ci ty by redu ci ng manual effort, im pro v ing test and release visibility, and applying AI to engineering pro cesses.

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 im pro v ing release readiness, software quality, and engineering pro ductivity. 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 im pro v e engineering pro ductivity and de ci sion-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 pro cesses and measure im pro v e ments in cycle time, test effi ci ency, defect prevention, and engineering throughput.
• Im pro v e visibility into test health, regression trends, flaky tests, failure patterns, and release readiness.
• Collaborate with engineering, QA, operations, data, and pro gram 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, pro cess im pro v e ments, and measurable business impact to engineering and leadership stakeholders.

What You Must Have

• Strong pro fi ci ency in Python and SQL .
• Pro v e n 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 im pro v e engineering pro ductivity, test analysis, defect triage, documentation, or de ci sion-making.
• Ability to evaluate AI-generated outputs for accuracy, consistency, traceability, and usefulness in engineering workflows.
• Strong analytical, debugging, and pro blem-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 S ci ence, 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 pro cesses 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 Pro jects, or similar tools into automated release tracking, workflow orchestration, or engineering triage