Senior Software Engineer – AI Engineering, Productivity

General Motors

. Develop data-intensive and AI-enabled software applications supporting Product Development engineering teams .

Posted 10/8/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing data-intensive and AI-enabled software applications, with a strong focus on backend services, data pipelines, and performance optimization. Proficient in collaborating within Agile/SCRUM environments and applying software engineering best practices to ensure high-quality deliverables.

Highest-signal resume keywords

Java DevelopmentPython DevelopmentSQL Query OptimizationKubernetes/Docker ExperienceDatabricks Data Pipeline Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQL QueriesData TransformationsBackend Services DevelopmentAPI DevelopmentData ModelingPerformance TuningETL/ELT ProcessesAutomated TestingCI/CD PipelinesObservability Practices

Soft Skills

Problem-SolvingCommunicationMentoringCollaborationOwnership

Tools & Technologies

DatabricksKubernetesDockerQuarkusAngularPostgreSQLAzureAWSGCPGit/GitHub

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster’s Degree in Computer Science (Preferred)

Industry Keywords

AI/ML SolutionsData GovernanceAgile/SCRUMSoftware Engineering Best PracticesData Quality

Tech Stack

Tools & technologies

AngularAWSAzureCloudDockerETLGoogle Cloud PlatformJavaKubernetesPostgresPythonSparkSQL

About the role

Key responsibilities & impact

Develop data-intensive and AI-enabled software applications supporting Product Development engineering teams
Design, develop, and maintain data-driven applications and services
Write performant SQL queries, functions, and stored procedures for complex data transformations and modeling
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
Develop enterprise applications using Kubernetes/Docker, Quarkus, Java, Angular, PostgreSQL, and GM-approved tools
Partner with data science and AI teams to productionize AI/ML and LLM-based solutions
Identify and remediate code quality, performance, security, and data-correctness issues
Lead or contribute to solution architecture, patterns, and technology choices aligned with GM standards
Apply software engineering best practices including code reviews, automated testing, branching strategies, CI/CD, observability, and secure coding
Collaborate with product owners, data engineers, architects, and business stakeholders in an Agile/SCRUM environment
Troubleshoot production issues across data, application, and infrastructure layers and perform root cause analysis
Remove project roadblocks and keep delivery on track
Guide and mentor software engineers and team members
Document software and data solutions according to GM standards

Requirements

What you’ll need

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 data-centric applications on distributed or cloud platforms such as Databricks or Spark
3+ years of experience with Kubernetes/Docker, Quarkus, and cloud platforms such as Azure, AWS, or GCP
Experience working in Agile/SCRUM development methodologies
Hands-on experience with Git/GitHub, code reviews, automated builds, automated testing, and CI/CD pipelines
Willingness and demonstrated ability to learn and apply AI concepts, including AI/ML and LLM-based solutions
Strong problem-solving skills
Excellent written and verbal communication skills
Demonstrated ownership, accountability for quality, and focus on measurable value
GM does not provide immigration-related sponsorship; candidates must not require GM immigration sponsorship now or in the future
Master’s Degree in Computer Science, Engineering, Information Systems, or a related field is preferred
Preferred: 10+ years of experience delivering enterprise-grade or global, scalable software applications
Preferred experience with Databricks, Spark, Azure/cloud migrations, AI/ML initiatives, data modeling, data quality, metadata management, data governance, observability, reliability practices, technical standards, and mentoring

Benefits

Comp & perks

Relocation benefits are available for candidates who qualify under company policy
GM Total Rewards benefits supporting well-being at work and at home