Senior Software Engineer - AI Engineering and Productivity

• Design, develop, and maintain data driven and AI-enabled applications and services that support Product Development engineering teams
• Write high-quality, performant SQL (queries, functions, stored procedures) for complex data transformations and modeling across enterprise data platforms (e.g., SQL Server, Oracle, PostgreSQL)
• Build and optimize data pipelines and workflows in Databricks (DBX) and related tools to support batch and near realtime 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 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 based solutions, including feature pipelines, inference integrations, monitoring, and continuous improvement
• Proactively identify and remediate issues related to code quality, patterns, performance, security, and data correctness, using code quality analysis tools 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 and champion software engineering best practices, including code reviews, automated testing, branching strategies, CI/CD pipelines (e.g., GitHub Actions), observability, and secure coding practices
• Collaborate with cross-functional teams (product owners, data engineers, architects, business stakeholders) to refine requirements, define acceptance criteria, and deliver incremental value in an Agile/SCRUM environment
• Troubleshoot and resolve production issues across the full stack (data, application, infrastructure), driving root cause analysis, stable fixes, and clear documentation
• Navigate complex corporate processes to remove project roadblocks and keep delivery on track
• Provide guidance and mentoring to fellow software 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 and can be leveraged across VEQ and PD Business Systems

• Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related field, OR equivalent experience
• 6+ years of experience delivering enterprise or full stack software solutions using Java / JEE, Python , and preferably Angular
• 3+ years of experience working with complex SQL queries, functions, and stored procedures, including performance tuning and optimization against large datasets
• Experience building or supporting data pipelines , ETL/ELT processes, or datacentric applications on distributed or cloud platforms (e.g., Databricks, Spark , or similar)
• 3+ years of experience with Kubernetes/Docker, Quarkus , and cloud platforms such as Azure, AWS , or GCP
• 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 (e.g., GitHub Actions)
• Willingness and demonstrated ability to learn and apply AI concepts , including working with data and APIs that support AI/ML and LLM based solutions
• 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 nontechnical stakeholders
• Demonstrated ownership mindset, accountability for quality, and focus on delivering measurable value to internal customers

• Master’s Degree in Computer Science, Engineering, Information Systems, or a related field
• 10+ years of experience delivering enterprise grade or global, scalable software applications , including data intensive or analytics focused solutions
• Deep hands on experience with Databricks (Delta tables, notebooks, jobs, 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 use of managed data, messaging, and API services
• Experience working with or supporting AI/ML initiatives (e.g., feature engineering, model integration, AI/LLM service integration, monitoring, and ML Ops concepts)
• Knowledge of relational and dimensional data modeling, data quality practices, metadata management, and data governance in an enterprise environment
• Experience with observability and reliability practices (logging, metrics, tracing, dashboards, alerting, 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

Relocation benefits