AI Agent 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 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 a culture of exploration, caretaking, and hard work. We respect the past and the future by electrifying and digitizing an iconic American brand, loading it with innovation, and creating vehicles that are equally at home at a campsite, a job site, or on a Tuesday commute. Our vehicles feature two powertrains: an all-electric option and 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.

About the role

Become part of an iconic brand that is set to revolutionize the electric pick-up truck and rugged SUV marketplace. You will design, develop, and deploy AI agents on Databricks, owning the full lifecycle from prototyping to production—including versioning, monitoring, and maintenance of multiple agents running in parallel.

Responsibilities

• Build and maintain robust evaluation frameworks using MLflow's evaluation suite, implementing and customizing judges (built-in, guideline-based, and custom) to systematically assess agent quality across correctness, safety, and business-specific criteria.
• Drive continuous quality improvement of AI agents through structured offline evaluation pipelines (curated datasets, benchmarks) and online production monitoring, leveraging MLflow tracing to understand agent execution patterns.
• Collect, structure, and incorporate human feedback from diverse stakeholder groups (engineering, quality, business) into evaluation workflows and agent improvement cycles.
• Collaborate with Data Engineers, IT, and R&D to define data configurations and pipelines that feed AI agents with reliable, high-quality inputs.
• Leverage and combine multiple data sources (on-site, off-site, connected vehicle data) to build agents that identify trends, anomalies, and quality signals at scale.
• Surface agent outputs and quality insights to Quality business stakeholders through dashboards and visual reporting tools, translating complex model behavior into understandable and actionable information.
• Identify and close data quality gaps, ensuring that data feeding into agents is clean, consistent, and continuously improving through well-defined requirements and automated checks.

Requirements

• Bachelor's Degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related field—or equivalent practical experience.
• 4+ years of experience in MLOps, AI/ML engineering, or data engineering in production environments.
• Experience designing and executing evaluation workflows for non-deterministic AI systems, including both offline (dataset-based) and online (production monitoring) evaluation strategies.
• Solid understanding of LLM concepts relevant to agent quality: hallucination, grounding, retrieval quality, tool use reliability, safety.

Skills

Technical Skills

• Hands-on experience developing and deploying AI agents on Databricks (Mosaic AI / Databricks Agent Framework), including multi-agent architectures and agent lifecycle management.
• Deep expertise in MLflow: Tracking, Model Registry, Deployments, Evaluation framework (built-in, guideline & custom judges), and Tracing for agent observability.
• Strong proficiency in Python and agent development frameworks (e.g., LangChain, LlamaIndex, AutoGen, or similar).
• Proficiency in SQL and cloud-based storage systems (Delta Lake, Unity Catalog, or equivalent).
• Familiarity with CI/CD practices for ML systems (model versioning, automated testing pipelines, deployment gates).
• Experience with BI tools (e.g., Sigma, PowerBI) (nice to have).
• Experience building RAG pipelines including Vector Store integration (e.g., Databricks Vector Search), embedding models, and chunking strategies (nice to have).
• Familiarity with Streamlit or Gradio for lightweight internal tooling (nice to have).
• Knowledge of responsible AI / AI governance frameworks (nice to have).

Soft Skills & Ways of Working

• Strong communication skills—able to translate technical evaluation results into clear, business-relevant insights for quality and engineering stakeholders.
• Structured problem-solving mindset with the ability to define methodologies, prioritize independently, and drive assignments to completion with minimal supervision.
• Comfortable operating in multidisciplinary, fast-moving environments with ambiguous requirements.
• Growth mindset—eager to stay current with the rapidly evolving AI agent and LLMOps landscape.

Location & Travel

This role may be based out of the Scout Motors corporate headquarters in Charlotte, NC. It requires 4-5 days per week in the office, with regular in-person meetings and events. Applicants should expect to convene with Scout colleagues in person and travel occasionally to participate in events on behalf of the company.

Benefits

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

Pay

This is a full-time, exempt position eligible for a base salary and participation in an annual performance bonus program. The final salary offered will be determined based on the candidate's skills and experience. The annual performance bonus program is preset and not candidate-dependent. Initial base salary range: $95,000.00 - $120,000.00.