AI Engineering Manager Jobs
AI Engineering Manager jobs are open across tech, fintech, healthtech, and enterprise software, at levels from senior engineer to director, with specializations in MLOps, generative AI, and applied machine learning infrastructure. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 969+ AI Engineering Manager jobs
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience in software engineering leadership in ML Infrastructure, ML, or product-focused AI.
- 5 years of experience with large scale distributed systems.
- 2 years of experience in a people management or team leadership role.
- Experience with Generative AI lifecycle, including Agent frameworks or protocols (e.g., MCP, A2A), RAG, prompt engineering, or model evaluation systems.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Demonstrated experience architecting or contributing to simulation frameworks, evaluation infrastructure, or enterprise quality platforms.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Gemini Cloud Assist is designed to simplify how customers learn, design, deploy, and operate their services. Our goal is to establish intelligent AI agent as a primary interface for cloud operations, integrating seamlessly across the Cloud Console, IDEs, and other developer surfaces. In this role, you will focus on the Quality Flywheel, a foundational platform at the core of our AI quality strategy. You will build the end-to-end system that drives our agent’s continuous, automated improvement. This involves analyzing user interactions, implementing real-time evaluations to detect successes and failures, generating high-quality evaluation data, and creating feedback loops that drive model self-improvement and fine-tuning.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead a team of engineers, driving career growth, team culture, and execution across data collection, evaluation generation, and unified benchmarks.
- Act as Tech Lead for the Quality Flywheel, architecting systems for scalable data collection, realistic simulation environments, eval generation, and online hill climbing.
- Direct software design and implementation for next-gen evaluation infrastructure (Eval Infra), tooling, and Gemini post-training systems adhering to architectural best practices.
- Partner across teams to distill complex, ambiguous model and platform requirements into simplified, robust technical solutions.
- Drive overarching testing and reliability architecture, advocating production stability, test environment improvements, and on-call operational support.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience in software engineering leadership in ML Infrastructure, ML, or product-focused AI.
- 5 years of experience with large scale distributed systems.
- 2 years of experience in a people management or team leadership role.
- Experience with Generative AI lifecycle, including Agent frameworks or protocols (e.g., MCP, A2A), RAG, prompt engineering, or model evaluation systems.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Demonstrated experience architecting or contributing to simulation frameworks, evaluation infrastructure, or enterprise quality platforms.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Gemini Cloud Assist is designed to simplify how customers learn, design, deploy, and operate their services. Our goal is to establish intelligent AI agent as a primary interface for cloud operations, integrating seamlessly across the Cloud Console, IDEs, and other developer surfaces. In this role, you will focus on the Quality Flywheel, a foundational platform at the core of our AI quality strategy. You will build the end-to-end system that drives our agent’s continuous, automated improvement. This involves analyzing user interactions, implementing real-time evaluations to detect successes and failures, generating high-quality evaluation data, and creating feedback loops that drive model self-improvement and fine-tuning.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead a team of engineers, driving career growth, team culture, and execution across data collection, evaluation generation, and unified benchmarks.
- Act as Tech Lead for the Quality Flywheel, architecting systems for scalable data collection, realistic simulation environments, eval generation, and online hill climbing.
- Direct software design and implementation for next-gen evaluation infrastructure (Eval Infra), tooling, and Gemini post-training systems adhering to architectural best practices.
- Partner across teams to distill complex, ambiguous model and platform requirements into simplified, robust technical solutions.
- Drive overarching testing and reliability architecture, advocating production stability, test environment improvements, and on-call operational support.
AI Engineering Manager Jobs by Experience Level
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Find AI Engineering Manager JobsAI Engineering Manager Job Market
Who's Hiring
- JPMorganChase31
- Apple26
- Meta22
- Booz Allen Hamilton20
- Google17
Top Industries Hiring
- Technology & Software30
- Education12
- Consulting & Professional Services11
- Banking & Financial Services10
- Investment & Asset Management7
What Employers Look For
The qualifications that appear most often in AI engineering manager jobs.
- 5+ years of experience in machine learning or AI engineering roles
- Proven experience managing and growing engineering teams
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow
- Experience deploying and operating ML models in production environments
- Familiarity with MLOps tooling, model monitoring, and CI/CD pipelines for AI systems
- Bachelor's or master's degree in computer science, machine learning, or a related field
Tips for Your AI Engineering Manager Job Search
Quantify model impact on your resume
Hiring managers for ai engineering manager roles want to see outcomes, not just projects. Replace vague bullet points with metrics like latency improvements, cost reductions from model optimization, or team throughput gains tied directly to your leadership decisions.
Show both technical and people leadership
Many ai engineering manager candidates undersell one side. Your resume should show you can ship production ML systems and also hire, grow, and retain engineers. Dedicate space to both, with concrete examples of each on the same document.
Target roles by AI stack, not just title
Job listings vary widely between companies running LLM pipelines, computer vision systems, or classical ML at scale. Filter by the stack you know best, so your application speaks directly to what the team is actually building right now.
Apply early to roles that fit
Migrate Mate lists ai engineering manager openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a system design answer for ML platforms
Interviews for ai engineering manager roles almost always include a technical design round. Practice walking through how you would architect a feature store, model serving layer, or retraining pipeline, explaining your tradeoffs clearly to both engineering and product stakeholders.
Negotiate scope, not just compensation
When you receive an offer, ask about the team size you will own, the roadmap influence you will have, and whether you will be expected to stay hands-on technically. These factors determine your day-to-day experience more than the title on the offer letter.
AI Engineering Manager Jobs: Frequently Asked Questions
Which companies are hiring the most ai engineering managers?
The most active employers for ai engineering managers right now are JPMorganChase, Apple, and Meta, and the most openings are in California, Texas, and New York, based on current listings on Migrate Mate as of November 2026. Demand is especially concentrated at companies scaling generative AI and large language model applications into production.
How many ai engineering manager jobs are remote?
About 77% of ai engineering manager openings are fully remote or hybrid as of November 2026, reflecting strong demand for distributed AI leadership. Sub-areas like MLOps platform engineering and AI infrastructure tend to have higher remote availability than roles tied to in-person research labs or hardware-adjacent teams.
How do you become an ai engineering manager?
Start by building a strong foundation as an individual contributor in machine learning or AI engineering, then take on tech lead responsibilities to demonstrate you can guide a team technically. Develop people management skills by mentoring junior engineers and leading cross-functional projects. When pursuing management roles, emphasize both your ability to deliver production AI systems and your record of growing the engineers around you.
How do you get hired as an ai engineering manager with little experience?
Move into an informal lead role at your current company first by owning a project end to end and mentoring one or two engineers. Build a portfolio of production ML work that shows technical depth. When applying, target smaller companies or early-stage teams where the management layers are thinner and demonstrated technical ownership can outweigh years of formal management experience.
What does the ai engineering manager interview process look like?
The process typically includes a recruiter screen, a technical phone round focused on ML system design or coding, a people management round where you discuss how you have handled team conflicts or performance issues, and a final loop with engineering directors or cross-functional partners. Some companies also include a written or verbal case study on how you would build or scale an AI team.
Where can I find and apply to ai engineering manager jobs?
You can find and apply to ai engineering manager jobs on Migrate Mate, which lists current openings from across the United States. Search the roles available, find the ones that fit your background and the AI stack you work in, and apply directly to each listing from the page.
See All 969+ AI Engineering Manager Jobs
Find roles that match your experience and apply in just a few clicks.
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