> Markdown version of [/jobs/ext/2546199-ai-agent-engineer](https://www.wearedevelopers.com/jobs/ext/2546199-ai-agent-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Agent Engineer - **Company:** Scout Motors - **Location:** Charlotte, NC, United States (Remote available) - **Experience:** Experienced - **Salary:** $95,000.0 - $120,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Automation of Tests, Cloud Storage, Continuous Integration, Information Engineering, Python (Programming Language), Machine Learning, Power BI, Search Technologies, Software Engineering, SQL Databases, Management of Software Versions, Large Language Models, Multi-Agent Systems, Data Lakes, Information Technology, Machine Learning Operations, Tools for Reporting, Virtual Agents, Streamlit Framework, Software Version Control, Databricks - **Published:** August 27, 2026 - **Apply:** https://www.dice.com/job-detail/5618ae23-001c-401d-ae41-18b268efea9f ## About the Role 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, 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 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 ## Description Become part of an iconic brand that is set to revolutionize the electric pick-up truck & rugged SUV marketplace by achieving the following: * 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 * 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 Location & Travel Expectations: * This role may be based out of the Scout Motors corporate headquarters in Charlotte, NC. * 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. ## Related Videos - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [On a Secret Mission: Developing AI Agents](https://www.wearedevelopers.com/videos/1510-on-a-secret-mission-developing-ai-agents) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Enabling intelligent logistics automation: home-grown Industrial IoT platform at Austrian Post](https://www.wearedevelopers.com/videos/2018-enabling-intelligent-logistics-automation-home-grown-industrial-iot-platform-at-austrian-post) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) ## Related Articles - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [A 5-Step Open-Source Setup for Agentic Engineering](https://www.wearedevelopers.com/magazine/738-a-5-step-open-source-setup-for-agentic-engineering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)