Sr. Software Engineer - AI Engineering and Productivity
General Motors1 day ago
Warren, MI, USA or Austin, TX, USASenior
Responsibilities
- Design, develop, and maintain data-driven and AI-enabled applications and services for Product Development engineering teams.
- Write and optimize complex SQL queries, functions, stored procedures, transformations, and data models across enterprise data platforms.
- Build and optimize Databricks data pipelines and workflows for batch and near-real-time processing.
- Develop reusable Java and/or Python backend services and APIs integrating data, business rules, and user workflows.
- Build enterprise applications using Kubernetes, Docker, Quarkus, Java, Angular, PostgreSQL, and other approved tools.
- Partner with data science and AI teams to productionize AI/ML and LLM solutions, including feature pipelines, inference integrations, monitoring, and continuous improvement.
- Contribute to architecture, solution design, technology selection, coding standards, automated testing, CI/CD, observability, and secure coding practices.
- Troubleshoot production issues across data, application, and infrastructure layers and drive root-cause analysis and stable fixes.
- Collaborate with cross-functional stakeholders to refine requirements, define acceptance criteria, and deliver incremental value.
- Mentor software engineers and document solutions according to GM standards.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related field, or equivalent experience.
- At least 6 years of experience delivering enterprise or full-stack software solutions using Java/JEE and Python, preferably with Angular.
- At least 3 years of experience developing and optimizing complex SQL queries, functions, and stored procedures against large datasets.
- Experience with data pipelines, ETL/ELT processes, or data-centric applications on distributed or cloud platforms such as Databricks or Spark.
- At least 3 years of experience with Kubernetes/Docker, Quarkus, and cloud platforms such as Azure, AWS, or GCP.
- Experience with Agile/SCRUM development, backlog refinement, sprint planning, code reviews, automated builds, testing, and CI/CD pipelines.
- Ability to learn and apply AI concepts and work with APIs supporting AI/ML and LLM solutions.
- Strong problem-solving, communication, ownership, collaboration, and accountability skills.
- Preferred qualifications include a master’s degree, 10 or more years of enterprise software experience, deep Databricks or Spark expertise, cloud migration experience, AI/ML and LLM integration experience, data modeling and governance knowledge, observability and reliability experience, and the ability to influence technical direction and mentor engineers.
Benefits
- Hybrid work arrangement requiring the selected candidate to report to a specific location at least three times per week or as directed by the manager.
- Relocation benefits are available for candidates who qualify under company policy.
- GM provides a day-one benefits program supporting employee well-being at work and at home.
- GM offers reasonable accommodations for job seekers with disabilities.
Tech Stack
AngularApache SparkAWSAzureDatabricksDockerGitGitHub ActionsGoogle Cloud PlatformJavaKubernetesMicrosoft SQL ServerPostgreSQLPythonSQL
Categories
BackendData Engineering
About General Motors
General Motors designs, manufactures, and sells cars, trucks, and electric vehicles for consumers and commercial fleets under brands including Chevrolet, GMC, Cadillac, and Buick. A public company on the NYSE headquartered in Detroit and founded in 1908, it operates globally and is developing EVs on its Ultium battery platform. Revenue comes from vehicle and parts sales, connected services such as OnStar, and financing through GM Financial.