Interested in this AI Agent Developer role at Scout Motors?
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About This Role
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!
#### What you'll do
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.
#### What you'll bring
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
#### What you'll gain
The benefits of joining Scout include the chance to build products and a company from the ground up. This is a chance to create something new and lasting – with an iconic brand at its foundation. In addition, Scout provides competitive compensation and benefits to support your physical, mental, and financial wellbeing. Program specifics are detailed in company policies and employee benefit guides, select highlights:
- Competitive insurance including:
+ Medical, dental, vision and income protection plans
- 401(k) program with:
+ An employer match and immediate vesting
- Generous Paid Time Off including:
+ 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 Transparency
This is a full\-time, exempt position eligible to receive a base salary and to participate in an annual performance bonus program. Final salary offered will be determined based on factors including but not limited to 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
Internal Leveling Code: IC9
Notice to applicants:
- To be considered for career opportunities at Scout Motors, applicants must be 18 years of age or older.
- Residing in San Francisco: *Pursuant to the San Francisco Fair Chance Ordinance, Scout Motors will consider for employment qualified applicants with arrest and conviction records.*
- Residing in Los Angeles: *Scout Motors will consider for employment qualified applicants with criminal histories in a manner consistent with the Los Angeles Fair Chance Initiative for Hiring Ordinance.*
- Residing in New York City: *This role is not eligible for remote work in New York City.*
Equal Opportunity
Scout Motors is committed to employing a diverse workforce and is proud to be an Equal Opportunity Employer. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, disability, pregnancy, or any other characteristics protected by law. Scout Motors is committed to compliance with all applicable fair employment practice laws. If you require reasonable accommodation to complete a job application, pre\-employment testing, or a job interview or to otherwise participate in the hiring process, please contact [email protected].
Salary Context
This $95K-$120K range is in the lower quartile for AI Agent Developer roles in our dataset (median: $192K across 41 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 3,823 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Scout Motors, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $245,040 based on 106 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($107K) sits 56% below the category median. Disclosed range: $95K to $120K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Scout Motors AI Hiring
Scout Motors has 2 open AI roles right now. They're hiring across AI Agent Developer, AI/ML Engineer. Based in Charlotte, NC, US. Compensation range: $120K - $170K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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