Sr. Software Engineer - Design and R&D

General Motors • Warren, MI

3d • Hybrid

About The Position

The Global Design and R&D IT team supports the design and research and development of GM production and concept vehicles, from early innovation through production design. The Sr. Software Engineer develops data-intensive and AI-enabled applications for Global Design and Research & Development teams, delivering reliable and scalable solutions using SQL, Databricks, Java, Python, and other modern technologies. The role emphasizes data quality, performance, security, and operational reliability.

The engineer helps shape how teams access and use data and AI, contributes patterns and best practices for SQL, Databricks, and AI/ML integrations, and supports modernization and cloud initiatives. The role also includes technical leadership, mentorship, cross-functional collaboration, solution documentation, and production support.

This role is categorized as hybrid. The selected candidate is expected to report to a specific location at least three times a week or at another frequency set by their manager. Relocation benefits are available to candidates who qualify under company policy. GM does not provide immigration-related sponsorship for this role.

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 software, data, or platform solutions using Java, Python, or comparable modern programming languages.
• Experience designing and operating production applications using APIs, relational databases, cloud services, and containerized environments.
• Experience building or supporting data pipelines, ETL/ELT processes, or data-intensive applications using Databricks, Spark, or comparable distributed data platforms.
• Experience integrating AI/ML services, LLM APIs, or model-driven capabilities into production applications, including data preparation, integration, evaluation, monitoring, security, and responsible-use considerations.
• Experience with Docker and Kubernetes and at least one major cloud platform, such as Azure, AWS, or GCP.
• Experience with Quarkus or a comparable modern Java application framework.
• Experience with Agile/Scrum methodologies, including backlog refinement, sprint planning, and incremental delivery.
• Hands-on experience with modern DevOps practices such as Git/GitHub, code reviews, automated builds, automated testing, and CI/CD pipelines.
• Strong problem-solving skills, including the ability to break down complex technical and data challenges into actionable steps and deliver high-quality solutions.
• Excellent written and verbal communication skills and ability to collaborate with technical and non-technical stakeholders.
• Demonstrated ownership, accountability for quality, and focus on delivering measurable value to internal customers.

Nice To Haves

• Master's degree in Data Science, Data Engineering, Computer Science, Software Engineering, Engineering, Information Systems, or a related field.
• Extensive experience delivering enterprise-grade or globally scalable software applications, including data-intensive or analytics-focused solutions.
• Deep hands-on experience with Databricks, including Delta tables, notebooks, jobs, and workflows, and/or Spark for data engineering, analytics, or AI workloads.
• Experience migrating applications and complex data workloads to Azure or other cloud platforms, including managed data, messaging, and API services.
• Experience supporting AI/ML initiatives, including feature engineering, model integration, AI/LLM service integration, monitoring, and MLOps concepts.
• Knowledge of relational and dimensional data modeling, data quality practices, metadata management, and enterprise data governance.
• Experience with product lifecycle management (PLM), digital engineering, visualization, CAD/CAM, simulation, or design technology platforms.
• Experience with observability and reliability practices, including logging, metrics, tracing, dashboards, alerting, and SRE concepts for data and application services.
• Demonstrated ability to influence technical direction, establish reusable patterns and standards, and mentor less experienced engineers.
• Ability to manage multiple initiatives and priorities in a fast-paced environment while maintaining high engineering standards.

Responsibilities

• Design, develop, and maintain data-driven and AI-enabled applications and services for Product Development engineering teams.
• Write performant SQL queries, functions, and stored procedures for complex transformations and modeling across enterprise platforms such as SQL Server, Oracle, and PostgreSQL.
• Build and optimize Databricks data pipelines and workflows for batch and near-real-time processing.
• Develop backend services and APIs in Java and/or Python that integrate data, business rules, and user workflows.
• Develop and operate enterprise-grade applications and services using technologies such as Java, Python, Quarkus, PostgreSQL, Docker, Kubernetes, Angular, and React, in accordance with enterprise standards.
• Partner with data science and AI teams to productionize AI/ML and LLM solutions, including data preparation, feature pipelines, inference integrations, evaluation, monitoring, and continuous improvement.
• Identify and remediate issues involving code quality, architecture, design patterns, performance, security, and data correctness using analysis, testing, profiling, and observability practices.
• Lead or contribute to solution design, architecture, patterns, and technology choices aligned with GM standards and its Statement of Technical Direction.
• Apply and champion engineering practices including code reviews, automated testing, branching strategies, CI/CD, observability, and secure coding.
• Collaborate with product owners, data engineers, architects, and business stakeholders to refine requirements, define acceptance criteria, and deliver incremental value in an Agile/Scrum environment.
• Troubleshoot production issues across data, application, and infrastructure layers; drive root-cause analysis, stable fixes, and clear documentation.
• Navigate enterprise processes, dependencies, and governance requirements to remove roadblocks and maintain delivery progress.
• Guide and mentor software engineers and team members in SQL, Databricks, cloud, and AI-related technologies.
• Document software and data solutions to GM standards for use across business functions as applicable.
• Participate in production support and operational readiness, including incident response, service-level objective planning, release readiness, monitoring, and continuous improvement.

Benefits

• Relocation benefits are available for candidates who qualify under company policy.
• GM describes benefits and well-being support through its Total Rewards resources; specific benefits are not listed in the posting.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior