Sr. Software Engineer - Design and RD

The Role

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. We are seeking a highly motivated Sr. Software Engineer to develop data-intensive and AI-enabled applications supporting Global Design and Research & Development teams.

This role will work with complex data requirements and deliver reliable, scalable solutions using SQL, Databricks, Java, Python, and other modern technologies. You will design and build software and data solutions with a strong focus on data quality, performance, security, and operational reliability.

You will also advise, coach, and mentor software engineers while helping shape how engineering teams access and use data and AI. You will contribute to patterns and best practices for SQL, Databricks, AI/ML integrations, and ongoing modernization and cloud initiatives.

What You'll Do

• Design, develop, and maintain data-driven and AI-enabled applications and services that support Product Development engineering teams.
• Write high-quality, performant SQL, including queries, functions, and stored procedures, for complex data transformations and modeling across enterprise data platforms such as SQL Server, Oracle, and PostgreSQL.
• Build and optimize data pipelines and workflows in Databricks and related tools to support batch and near-real-time data processing.
• Develop backend services and APIs in Java and/or Python that integrate data, business rules, and user workflows into robust, reusable components.
• Develop and operate enterprise-grade applications and services using appropriate combinations of Java, Python, Quarkus, PostgreSQL, Docker, Kubernetes, Angular, React, and approved enterprise technology standards.
• Partner with data science and AI teams to bring AI/ML and large-language-model (LLM) solutions into production, including data preparation, feature pipelines, inference integrations, evaluation, monitoring, and continuous improvement.
• Proactively identify and remediate issues related to code quality, architecture and design patterns, performance, security, and data correctness using code analysis, testing, profiling, and observability practices.
• Lead or contribute to solution design, including architecture, patterns, and technology choices aligned with GM standards and the Statement of Technical Direction.
• Apply and champion software engineering best practices, including code reviews, automated testing, branching strategies, CI/CD pipelines, observability, and secure coding practices.
• 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 and resolve production issues across the data, application, and infrastructure stack by driving root-cause analysis, stable fixes, and clear documentation.
• Navigate enterprise processes, dependencies, and governance requirements to remove roadblocks and keep delivery on track.
• Provide guidance and mentorship to software engineers and team members, helping grow skills in SQL, Databricks, cloud, and AI-related technologies.
• Document software and data solutions so that technical documentation meets GM standards and can be leveraged 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.

Your Skills & Abilities (Required Qualifications)

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related field, or equivalent experience.
• 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, API or model 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 working in Agile/Scrum development 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 with the ability to break down complex technical and data challenges into clear, actionable steps and deliver high-quality solutions.
• Excellent written and verbal communication skills, with the ability to collaborate with both technical and non-technical stakeholders.
• Demonstrated ownership, accountability for quality, and focus on delivering measurable value to internal customers.

What Will Give You a Competitive Edge (Preferred Qualifications)

• 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 .
• Proven 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 data governance in an enterprise environment.
• Experience working 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.