AI Product Manager Jobs
22 ai pm jobs available
Staff Product Manager, AI Personalization - Careers at Airbnb
Airbnb
Head of Product Engineering (Retail)
ClearCourse
Data & AI Product Owner
Stellantis
SailPoint Product Owner
VIQU IT Recruitment
Head/Director of Product (AI Insights & Automation)
Mimica
Gen AI Product Manager - Lorien Impellam
Lorien Impellam
Head of Product - Dairy
Yeo Valley
AI Technical Product Manager
IO Associates
AI Technical Product Manager
IO Associates
Head of Product - Agriculture AI / Senior Product Manager
Precision AI
Product Owner AI
Picture More
CortAIx UK Factory Product Owner
Thales
Director, Data Product Owner & Data Modeling (HR / Finance / Client Domains)
BlackRock
Product Manager AI & Transformation
KEYSTONE EMPLOYMENT GROUP NO.1 LIMITED
Program Manager Fulfillment Operations
SupplyHouse.com
AI Product Owner
Nutrien
Product Manager, Sustainable - London Stock Exchange Group
London Stock Exchange Group
Senior Product Manager - AI
MCS Group
Senior Product Manager - CoreAI
Microsoft
Senior Product Manager - CoreAI
Microsoft
Frequently Asked Questions
What does an AI Product Manager do?
AI Product Managers define strategy and roadmap for AI/ML products. They work closely with ML engineers and data scientists to translate business problems into ML solutions. Responsibilities include defining success metrics, managing model performance, handling AI ethics/safety, and communicating AI capabilities to stakeholders. They bridge the gap between technical ML teams and business objectives.
What is the salary for AI Product Managers?
AI Product Managers typically earn 10-20% more than general PMs due to specialized skills. Salaries range from $150,000-$250,000 for mid-level roles and $200,000-$350,000+ for senior positions at top AI companies. Companies like OpenAI, Anthropic, Google DeepMind, and well-funded AI startups offer the highest compensation packages.
Do AI Product Managers need to know how to code?
While not required, technical skills are highly valued. AI PMs should understand ML fundamentals (supervised vs unsupervised learning, model training, evaluation metrics), be comfortable with data analysis (SQL, Python basics), and understand AI/ML system architecture. You don't need to build models, but you should be able to communicate effectively with ML engineers.
How do I transition to AI Product Management?
Start by learning ML fundamentals through courses (Andrew Ng's ML course, fast.ai). Build projects using AI APIs (OpenAI, Anthropic). Get experience at your current company with AI/ML features. Consider roles at AI-adjacent companies before pure AI companies. Networking with AI PMs and contributing to AI product communities helps build credibility.