AI Infrastructure Engineer

Here at Scout Motors, we're carrying forward the heritage of one of the most iconic American vehicles in history. A vehicle dating back to 1960. One that forged the path for future generations of rugged SUVs and trucks and will do so once again.

But Scout is more than just a brand, it’s a legacy steeped in a culture of exploration, caretaking, and hard work.

The Scout brand is all about respect. Respect for the past and the future by taking an iconic American brand that hasn’t been around for a while, electrifying it, digitizing it, and loading it with American innovation. Respect for communities by creating a company that stands for its people and its customers. Respect for both work and play, with vehicles that are equally at home at a camp site, a job site, or on a Tuesday commute.

And respect for our customers by developing two powertrains that meet their requirements — an all-electric powertrain as well as the Harvester™ range extender powertrain which includes a built-in gas-powered generator with an estimated 500 miles of combined range.

At Scout Motors, we empower our talented, inclusive, and entrepreneurial teams to innovate. What makes a Scout employee? Someone who is a visionary and a leader, who seeks new paths and shares lessons learned. A knowledgeable doer who collaborates across the company to build better. A go-getter with unrivaled passion.

Join us at Scout Motors and be part of shaping the future of transportation. If you're ready to drive change and make history, apply now!

Become part of an iconic brand that is set to revolutionize the electric pick-up truck & rugged SUV marketplace by achieving the following:

• 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.
• This role will be based out of the Scout Motors corporate headquarters in Charlotte, NC
  . This role may be remote to start but will transition to an in-office setting at the headquarters within 3-6 months of start date. This role is not eligible for remote work in New York City.
• This role requires 4-5 days per week in the office, with regular in-person meetings and events.
• Applicants should expect that the role will require the ability to convene with Scout colleagues in person and travel to participate in events on behalf of the company from time to time.

We expect all Scout employees to have integrity, curiosity, resourcefulness, and strive to exhibit a positive attitude, as well as a growth mindset. You’ll be comfortable with change and flexible in a fast-paced, high-growth environment. You’ll take a collaborative approach to achieve ambitious goals. Here's what else you'll bring:

• Bachelor's degree in computer science, information technology, or related field or equivalent work experience.
• 7+ years 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.
• Experience designing and orchestrating agentic automation workflows.
• Strong experience with Terraform and Infrastructure-as-Code.
• Expertise with cloud platforms such as AWS.
• Expertise with CI/CD tooling (Git Hub Actions, Git Lab CI).
• Strong Knowledge of Kubernetes and…