Senior Software Engineer (AI Engineering)

TL;DR

Senior Software Engineer (AI Engineering): Developing data-intensive and AI-enabled software applications for Product Development engineering teams with an accent on SQL, Databricks, and modern programming languages. Focus on productionizing AI/ML and LLM based solutions, optimizing data pipelines, and building robust backend services.

Location: Hybrid; must report to office in Austin, Texas or Warren, Michigan at least 3 times a week

Company

A global automotive leader striving for a world with Zero Crashes, Zero Emissions, and Zero Congestion.

What you will do

• Design, develop, and maintain AI-enabled applications and services using Java, Python, and Angular.
• Write high-performance SQL and optimize complex data transformations on enterprise data platforms.
• Build and optimize data pipelines and workflows in Databricks for batch and near real-time processing.
• Productionize AI/ML and LLM based solutions, including feature pipelines and inference integrations.
• Develop enterprise-grade applications using Kubernetes, Docker, and Quarkus on cloud platforms like Azure, AWS, or GCP.
• Mentor fellow engineers and champion software engineering best practices, including CI/CD via GitHub Actions.

Requirements

• 6+ years of experience delivering enterprise software solutions using Java, Python, and preferably Angular.
• 3+ years of experience with complex SQL performance tuning and optimization against large datasets.
• Experience with data pipelines, ETL/ELT processes, and distributed platforms like Databricks or Spark.
• 3+ years of experience with Kubernetes/Docker, Quarkus, and major cloud platforms (Azure, AWS, or GCP).
• Must not require immigration sponsorship now or in the future.
• Bachelor's Degree in Computer Science, Software Engineering, or a related field.

Nice to have

• Master's Degree in Computer Science or Engineering.
• 10+ years of experience with global, scalable software applications.
• Deep expertise in Databricks (Delta tables, notebooks, jobs, workflows).
• Experience with MLOps concepts, observability, and SRE practices.

Culture & Benefits

• Hybrid work environment with specified office attendance.
• Eligibility for relocation benefits may apply.
• Commitment to inclusion, belonging, and non-discrimination.
• Comprehensive Total Rewards package focusing on employee well-being.