AI Engineering Manager
AI Engineering Managers lead teams of AI/ML engineers to deliver AI products and systems. They balance technical excellence with people management, ensuring teams deliver impactful AI solutions.
What is a AI Engineering Manager?
AI Engineering Managers lead teams of AI/ML engineers to deliver AI products and systems. They balance technical excellence with people management, ensuring teams deliver impactful AI solutions.
Education Required
Bachelor's or Master's in Computer Science; engineering management experience
Certifications
- • Engineering Management
- • ML Certification
Job Outlook
Strong demand as AI teams scale. Technical leadership is valued.
Key Responsibilities
Lead AI engineering teams, deliver AI projects, hire and develop talent, set technical direction, collaborate with product, and ensure quality.
A Day in the Life
Required Skills
Here are the key skills you'll need to succeed as a AI Engineering Manager.
Engineering Management
Managing engineering teams
Hiring
Recruiting and hiring
AI/ML Technical
Technical AI/ML skills
People Management
Managing people
Communication
Effective communication skills
Project Management
Managing projects and timelines
Salary Range
Average Annual Salary
$240K
Range: $180K - $300K
Salary by Experience Level
Projected Growth
+45% over the next 10 years
ATS Resume Keywords
Optimize your resume for Applicant Tracking Systems (ATS) with these AI Engineering Manager-specific keywords.
Must-Have Keywords
EssentialInclude these keywords in your resume - they are expected for AI Engineering Manager roles.
Strong Keywords
Bonus PointsThese keywords will strengthen your application and help you stand out.
Keywords to Avoid
OverusedThese are overused or vague terms. Replace them with specific achievements and metrics.
💡 Pro Tips for ATS Optimization
- • Use exact keyword matches from job descriptions
- • Include keywords in context, not just lists
- • Quantify achievements (e.g., "Improved X by 30%")
- • Use both acronyms and full terms (e.g., "ML" and "Machine Learning")
How to Become a AI Engineering Manager
Follow this step-by-step roadmap to launch your career as a AI Engineering Manager.
Build Technical Foundation
Get 5+ years as ML engineer with deep technical expertise.
Develop Leadership Skills
Lead projects, mentor engineers, and drive technical decisions.
Learn People Management
Study hiring, performance management, career development.
Understand Business
Learn to translate business needs into technical roadmaps.
Practice Communication
Develop skills in stakeholder management and cross-functional work.
Transition to Management
Take on team lead roles and formal management positions.
🎉 You're Ready!
With dedication and consistent effort, you'll be prepared to land your first AI Engineering Manager role.
Portfolio Project Ideas
Build these projects to demonstrate your AI Engineering Manager skills and stand out to employers.
Build and scale ML team from 3 to 15 engineers
Deliver major AI product on time and budget
Establish engineering practices and culture
Improve team retention and satisfaction metrics
Drive technical strategy and architecture decisions
🚀 Portfolio Best Practices
- ✓Host your projects on GitHub with clear README documentation
- ✓Include a live demo or video walkthrough when possible
- ✓Explain the problem you solved and your technical decisions
- ✓Show metrics and results (e.g., "95% accuracy", "50% faster")
Common Mistakes to Avoid
Learn from others' mistakes! Avoid these common pitfalls when pursuing a AI Engineering Manager career.
Trying to do all the technical work yourself
Not investing enough in people development
Poor communication with stakeholders
Ignoring team culture and morale
Over-committing team to unrealistic deadlines
What to Do Instead
- • Focus on measurable outcomes and quantified results
- • Continuously learn and update your skills
- • Build real projects, not just tutorials
- • Network with professionals in the field
- • Seek feedback and iterate on your work
Career Path & Progression
Typical career progression for a AI Engineering Manager
Junior AI Engineering Manager
0-2 yearsLearn fundamentals, work under supervision, build foundational skills
AI Engineering Manager
3-5 yearsWork independently, handle complex projects, mentor junior team members
Senior AI Engineering Manager
5-10 yearsLead major initiatives, strategic planning, mentor and develop others
Lead/Principal AI Engineering Manager
10+ yearsSet direction for teams, influence company strategy, industry thought leader
Ready to start your journey?
Take our free assessment to see if this career is right for you
Learning Resources for AI Engineering Manager
Curated resources to help you build skills and launch your AI Engineering Manager career.
Free Learning Resources
- •Engineering management blogs
- •The Manager Path book
- •Leadership resources
Courses & Certifications
- •Engineering Management courses
- •Leadership programs
Tools & Software
- •Jira
- •Slack
- •1-on-1 tools
- •Performance management systems
Communities & Events
- •Engineering management Slack
- •Leadership forums
- •Tech manager groups
Job Search Platforms
- •Tech company careers
- •Management recruiters
💡 Learning Strategy
Start with free resources to build fundamentals, then invest in paid courses for structured learning. Join communities early to network and get mentorship. Consistent daily practice beats intensive cramming.
Work Environment
Work Style
Personality Traits
Core Values
Is This Career Right for You?
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💡 Tip: Use our Resume Optimizer to tailor your resume for AI Engineering Manager positions before applying.