Sr. Software Engineer - AI Engineering and Productivity

Sr. Software Engineer to build data-intensive and AI-enabled applications for Product Development engineering teams.

Responsibilities

• Design, develop, and maintain data-driven and AI-enabled applications and services supporting Product Development engineering teams
• Develop high-quality, performant SQL including queries, functions, and stored procedures for complex data transformations and modeling across enterprise data platforms (e.g., SQL Server, Oracle, PostgreSQL)
• Build and optimize Databricks (DBX) data pipelines and workflows to enable batch and near real-time processing
• Create backend services and APIs in Java and/or Python that integrate data, business rules, and user workflows into reusable components
• Develop enterprise-grade applications using Kubernetes/Docker, Quarkus, Java, Angular, PostgreSQL, and other GM-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
• Identify and remediate issues across code quality, patterns, performance, security, and data correctness using code quality analysis and remediation techniques
• Lead or contribute to solution design, including architecture, patterns, and technology choices aligned with GM standards and Statement of Technical Direction
• Apply software engineering best practices: code reviews, automated testing, branching strategies, CI/CD pipelines (e.g., GitHub Actions), observability, and secure coding practices
• Collaborate with cross-functional partners (product owners, data engineers, architects, business stakeholders) to refine requirements, define acceptance criteria, and deliver incremental value in Agile/SCRUM
• Troubleshoot and resolve production issues across the full stack (data, application, infrastructure), performing root cause analysis, implementing stable fixes, and documenting outcomes
• Navigate complex corporate processes to remove delivery roadblocks and keep progress on track
• Provide guidance and mentoring to engineers and team members, helping grow skills in SQL, Databricks, cloud, and AI-related technologies
• Document software and data solutions and ensure technical documentation meets GM standards for reuse across VEQ and PD Business Systems

Requirements

• Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related field, or equivalent experience
• 6+ years delivering enterprise or full stack software solutions using Java/JEE, Python, and preferably Angular
• 3+ years with complex SQL (queries, functions, stored procedures), including performance tuning/optimization on large datasets
• Experience building or supporting data pipelines, ETL/ELT, or datacentric applications on distributed/cloud platforms (e.g., Databricks, Spark, or similar)
• 3+ years with Kubernetes/Docker, Quarkus, and cloud platforms such as Azure, AWS, or GCP
• Experience with Agile/SCRUM (backlog refinement, sprint planning, incremental delivery)
• Hands-on DevOps practices: Git/GitHub, code reviews, automated builds, automated testing, and CI/CD pipelines (e.g., GitHub Actions)
• Ability to learn and apply AI concepts, including working with data and APIs supporting AI/ML and LLM-based solutions
• Strong problem solving to break down complex technical and data challenges into clear, actionable steps while delivering high-quality solutions
• Excellent written and verbal communication to collaborate with technical and nontechnical stakeholders
• Ownership mindset, accountability for quality, and focus on delivering measurable value to internal customers

Technologies

• SQL Server, Oracle, PostgreSQL, SQL
• Databricks (DBX), Spark, ETL/ELT
• Java, JEE, Python
• Kubernetes, Docker, Quarkus, Angular
• Azure, AWS, GCP
• AI/ML, LLM, CI/CD pipelines, Git, GitHub, GitHub Actions
• Agile/SCRUM

What Will Give You a Competitive Edge (Preferred Qualifications)

• Master’s Degree in Computer Science, Engineering, Information Systems, or a related field
• 10+ years experience delivering enterprise-grade or global, scalable applications, including data-intensive or analytics-focused solutions
• Deep hands-on experience with Databricks (Delta tables, notebooks, jobs, workflows) and/or Spark
• Proven experience migrating applications and complex data workloads to Azure or other cloud platforms, including managed data, messaging, and API services
• Experience working with or supporting AI/ML initiatives (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 enterprise environments
• Experience with observability and reliability practices (logging, metrics, tracing, dashboards, alerting, SRE concepts) for data and application services
• 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

Work Location / Hybrid

• Hybrid role based in Austin, TX
• Expect to report to a specific location at least 3 times a week (or as directed by your manager)

Relocation Benefits

• Relocation benefits available for candidates who qualify under company policy

Immigration Sponsorship

• GM does not provide immigration-related sponsorship for this role
• Do not apply if you will need GM immigration sponsorship now or in the future