Senior Software Engineer, Applied Analytics & Insights – Digital, Customer & Portfolio

Job Description

This role is based remotely but if you live within a 50-mile radius of an office [Atlanta, Austin, Detroit, Warren, or Mountain View], you are expected to report to that location three times a week, at minimum.

The Role 

We are looking for a full stack Senior Software Engineer to join the Applied Analytics & Insights - Digital, Customer & Portfolio organization, which focuses on leveraging data-driven solutions to optimize digital customer experiences and support strategic portfolio planning at GM.  In this position, you will collaborate with product owners, data scientists, and partner teams to design, develop, and implement analytics applications that improve customer experience and business outcomes, with an initial focus on vehicle portfolio planning use cases. 

What You’ll Do

• Collaborate with analytics delivery, data science, and stakeholder teams within a matrixed reporting structure to deliver applications that train and serve machine learning models.  
• Lead front-end and back-end software architecture, design, and development ensuring alignment with GM technology and security standards. 
• Implement software validation, testing, code review, documentation, and production monitoring processes to ensure user satisfaction, quality, and supportability. 
• Work with partner teams such as infrastructure, architecture, and operations on platform management and technology migrations as required. 
• Provide on-call support as required. 
• Keep up with new trends and technologies and actively seek ways to increase productivity, including using GenAI where appropriate.  
• Encourage continuous learning, knowledge sharing, and development within the team and the broader software engineering community. 

Your Skills & Abilities (Required Qualifications)

• Bachelor's degree (or equivalent work experience) in Computer Science, Data Science, or a related field. 
• Minimum of 5 years of hands-on experience delivering enterprise-scale software products, with an emphasis on integrating machine learning models and Databricks workflows. 
• Proven ability to lead engineering projects, mentor early-career developers, and collaborate effectively with data scientists, product managers, and non-technical stakeholders. 
• Advanced proficiency in both front-end development (React, Angular, TypeScript, HTML/CSS) and back-end development (Node.js, Python, or Java). 
• Deep understanding of hybrid-cloud and cloud-native software architecture, system design, and security, including microservices and containerization using Azure, Azure Key Vault, App Services, and Azure Kubernetes Services (or similar cloud platforms). 
• Experience with CI/CD processes, including automated builds, deployments, and pipeline development.