AI Infrastructure Engineer

About Scout Motors

We're carrying forward the heritage of one of the most iconic American vehicles in history—a brand dating back to 1960 that forged the path for future generations of rugged SUVs and trucks. Scout is more than just a brand; it’s a legacy steeped in exploration, caretaking, and hard work. We respect the past and future by electrifying and digitizing an iconic American brand, loading it with innovation, and offering two powertrains: an all-electric option and the Harvester™ range extender with an estimated 500 miles of combined range. At Scout Motors, we empower inclusive, entrepreneurial teams to innovate and shape the future of transportation.

Responsibilities

• Install, configure, and maintain AI platform and tools.
• Design, deploy, and operate infrastructure supporting ML and LLM workloads.
• Build, containerize, and deploy AI services using Docker.
• Build and maintain Machine Learning CI/CD pipelines for training, testing, and deployment.
• Deploy and manage AI services across cloud and on-prem environments.
• Automate infrastructure provisioning using Terraform and Infrastructure-as-Code best practices.
• Monitor system performance, reliability, and scalability of AI platforms.
• Implement observability for agentic AI systems to ensure reliability, transparency, and debuggability.
• Perform regular security updates, patching, access control, and vulnerability remediation.
• Integrate AI tools with APIs, data platforms, and internal systems.
• Research, evaluate, and prototype new AI, LLM, and MLOps tools.
• Troubleshoot infrastructure, data, and deployment issues.
• Research, test, and prototype emerging AI technologies.
• Document system architecture, deployment processes, and operational runbooks.

Location & Travel Expectations

This role is based at Scout Motors’ corporate headquarters in Charlotte, NC, and requires 4–5 days per week in the office. Regular in-person meetings and events are expected, along with occasional travel for company events.

Requirements

• Bachelor's degree in computer science, information technology, or related field, or equivalent work experience.
• 8+ years of practical experience with LLM platforms, LLMOps, and MLOps.
• Experience deploying and maintaining AI or data platforms in production.
• Hands-on experience with AI/automation tools and designing agentic automation workflows.
• Strong experience with Terraform and Infrastructure-as-Code.
• Proven experience deploying applications using Docker (Docker files, image optimization, container lifecycle).
• Expertise with cloud platforms such as AWS.
• Expertise with CI/CD tooling (GitHub Actions, GitLab CI).
• Strong knowledge of Kubernetes and orchestration.
• Solid understanding of networking.
• Experience supporting high-availability, production AI systems.
• Scripting skills (Python, PySpark, Bash).
• Knowledge of security best practices, patch management, and access controls.
• Collaborate with engineering, data, and product teams to support AI initiatives.
• Excellent problem-solving and troubleshooting skills.
• Effective communication and collaboration skills.
• A teaching and coaching approach to guiding engineers and teams.
• Minimum of a High School Diploma, GED, or equivalent.

Benefits

• Competitive insurance including medical, dental, vision, and income protection plans.
• 401(k) program with employer match and immediate vesting.
• Generous Paid Time Off: 20 days planned PTO (as accrued), 40 hours unplanned PTO, and 14 company/floating holidays annually.
• Up to 16 weeks of paid parental leave for biological and adoptive parents of all genders.
• Paid leave for bereavement, jury duty, voting time, or military leave.

Pay

This is a full-time, exempt position with a base salary range of $140,000–$170,000 and eligibility for an annual performance bonus program. Final salary is determined based on skills and experience.