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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:
The Manager, Data and AI Engineering is a hands\-on technical leader responsible for leading and developing a team of Data Engineers and AI Engineers while actively contributing to the design, development, and deployment of enterprise Data and AI solutions.
This person will lead multiple agile teams and drive the development of modern data platforms, AI\-enabled applications, intelligent agents, and Generative AI solutions while ensuring delivery excellence, scalability, security, governance, and operational support.
- Lead, mentor, and develop a team of Data Engineers, AI Engineers, and technical consultants.
- Establish team goals, performance expectations, career development plans, and technical growth initiatives.
- Foster a high\-performing engineering team environment focused on innovation, collaboration, quality, and continuous improvement.
- Provide technical guidance, coaching, and code reviews across Data Engineering and AI initiatives.
- Participate in recruiting, hiring, onboarding, and workforce planning activities.
- Architect, design, develop, and support scalable data platforms utilizing Databricks and cloud\-native technologies.
- Lead development of enterprise data pipelines and ETL/ELT processes supporting analytics, AI, and operational reporting.
- Drive data quality, governance, lineage, metadata management, and security practices.
- Lead the design and deployment of AI and Generative AI solutions that drive measurable business outcomes.
- Evaluate emerging AI technologies and recommend opportunities for business adoption aligned with team and enterprise objectives.
- Collaborate with Enterprise Architects to define platform standards and reference architectures.
- Ensure Data and AI solutions align with enterprise governance, cybersecurity, privacy, and compliance requirements.
- Drive platform scalability, reliability, resiliency, and operational readiness.
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, information technology, or related field or equivalent work experience.
- 7\+ years of experience in Data Engineering, Software Engineering, AI Engineering, or related technical disciplines.
- 3\+ years of experience leading technical teams and Agile delivery teams.
- Strong hands\-on experience designing and developing enterprise data solutions.
- Strong experience leading Data Engineering and AI Engineering teams.
- Experience managing cross\-functional technical teams through full software development lifecycles.
- Experience with AI tools and Platforms such as Databricks Data/AI Platform, Open WebUI, n8n, Pinecone, LangChain, LangGraph
- Experience with cloud platform technologies such as AWS or Azure, Docker, Kubernetes, CI/CD Pipelines, Monitoring and Observability Platforms (Data dog)
- Experience with Generative AI Solution Development, Retrieval\-Augmented Generation (RAG), Prompt Engineering, AI Agents and Agent Frameworks, Vector Databases (pinecone) and Large Language Models (LLMs)
#### 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
- Corporate Vehicle Program with:
+ Eligibility for 1 assigned vehicle
+ A mobility stipend
#### 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 \= $160,000\.00 \- $192,500\.00
Internal leveling code: M8
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 $160K-$192K range is below the median for AI Engineering Manager roles in our dataset (median: $185K across 13 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 4,317 AI roles we're tracking, AI Engineering Manager positions make up 0% of the market. At Scout Motors, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Engineering Manager roles pay a median of $244,000 based on 23 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($176K) sits 28% below the category median. Disclosed range: $160K to $192K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Scout Motors AI Hiring
Scout Motors has 2 open AI roles right now. They're hiring across AI Engineering Manager, AI/ML Engineer. Based in Charlotte, NC, US. Compensation range: $170K - $192K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Engineering Manager roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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