AI Product Manager Jobs

Discover the latest remote and onsite AI Product Manager roles across top active AI companies. Updated hourly.

Check out 532 new AI Product Manager opportunities posted on The Homebase

AI Product Manager

New
Top rated
Air Apps
Full-time
Full-time
Posted

As an AI Product Manager at Air Apps, you will define and drive the AI product roadmap to align with business objectives and user needs. You will collaborate with cross-functional teams such as engineering, design, and marketing to develop and launch AI-powered features. Your role includes conducting market research and analyzing user feedback to identify AI integration opportunities, working closely with data scientists and machine learning engineers to optimize AI models for accuracy, performance, and user impact, defining key performance indicators (KPIs) to measure success and iterating based on data-driven insights, staying up to date with AI trends and emerging technologies to keep products competitive, and ensuring ethical AI usage and compliance with data privacy regulations.

€58,000 – €73,000
Undisclosed
YEAR

(EUR)

Lisbon or Lisboa, Portugal
Maybe global
Onsite

Product Manager, Agent Memory

New
Top rated
Sierra
Full-time
Full-time
Posted

Lead development of Agent Memory, the system that enables AI agents to remember and personalize interactions across conversations, transforming one-off exchanges into continuous relationships that drive measurable business outcomes at scale. Balance competing stakeholder needs including end users expecting personalization, operations teams requiring compliance, and developers needing flexible integration patterns. Define how AI agents should remember, addressing session continuity, long-term relationships, intelligent consolidation, context retrieval, and privacy-preserving personalization. Collaborate closely with engineering teams on distributed systems, ML teams on retrieval and embedding technologies, and infrastructure teams on scalable storage solutions. Serve as a trusted and strategic advisor to customers in partnership with sales, go-to-market, and forward-deployed teams. Lead the product through all stages from concept to execution in collaboration with cross-functional partners.

$175,000 – $350,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite

Product Manager, Intelligence

New
Top rated
Sierra
Full-time
Full-time
Posted

Build the Intelligence Layer for Enterprise AI Agents by leading the development of Agent Intelligence, the decisioning system that enables AI agents to take optimal actions based on business context, user intent, and predicted outcomes. Transform reactive support into proactive, value-driving interactions at scale. Balance competing stakeholder needs among end users, operations teams, and developers. Define the architecture for AI agent decisioning, including real-time next-best-action selection and long-term outcome optimization, tackling problems such as contextual decisioning, multi-objective optimization, and interpretable AI reasoning. Collaborate with engineering on decisioning systems, ML teams on predictive models and reinforcement learning, and data teams on analytics and experimentation frameworks. Serve as a trusted and strategic advisor to customers in partnership with sales, go-to-market, and forward-deployed teams. Lead the product through all stages from concept to execution in close collaboration with cross-functional partners.

$175,000 – $350,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite

Tech Lead Manager, Billing and Insights

New
Top rated
Glean Work
Full-time
Full-time
Posted

Partner with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on Glean. Lead strategic reviews and advise customers on their AI roadmap, ensuring they get the most value from Gleans platform. Translate business needs into clear problem statements, success metrics, and practical AI solutions; collaborate with Product and R&D to shape priorities. Conduct discovery workshops, scope pilots, and guide rollouts, driving breadth and depth of adoption of the Glean platform. Design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. Proactively identify expansion opportunities and drive engagement across teams and functions.

$130,000 – $200,000
Undisclosed
YEAR

(USD)

United States
Maybe global
Remote

Staff Product Manager, AI/ML

New
Top rated
Firsthand
Full-time
Full-time
Posted

The Staff Product Manager is responsible for inventing, designing, and implementing novel solutions for the AI landscape within the Firsthand platform. This includes conceptualizing and designing new features using a data-informed approach and establishing clear metrics for success. The role also involves navigating ambiguity and change to collaboratively drive alignment with cross-functional teammates, working with enterprise customers and internal stakeholders to understand their needs and incorporate those insights into product decisions. Additionally, the manager must communicate product vision, strategy, and roadmap to key stakeholders, including senior leadership, to drive alignment and decision-making, and stay informed of industry trends, emerging technologies, and best practices to drive continuous improvement and innovation.

$195,000 – $210,000
Undisclosed
YEAR

(USD)

New York, United States
Maybe global
Hybrid

Product Manager

New
Top rated
Giga
Full-time
Full-time
Posted

The Product Manager is responsible for driving the product strategy and execution for AI agents that automate enterprise support and operations workflows, aiming to increase resolution rates from 60% to 98%. They own the development of self-improving agent platforms, multi-party real-time orchestration across voice, chat, and email, and no-code/low-code agent configuration tools including policy engines and scenario builders. They lead the expansion of products into regulated industries such as healthcare and financial services, ensuring compliance and integration with enterprise systems like Zendesk and Salesforce. The role involves defining roadmaps and priorities, shipping features that improve automation resolution rates, working closely with engineering on system architecture and AI model integration, collaborating cross-functionally with AI/ML engineers, design, sales, and customer success teams, and partnering with Fortune 100 customers to understand and address remaining challenges in automation. The Product Manager also focuses on technical product leadership, including sub-500ms latency requirements, API design, and developer experience for headless agents and integrations.

$250,000 – $400,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite

Group Product Manager - Noida

New
Top rated
Level AI
Full-time
Full-time
Posted

Own the platform portfolio including Agentic AI and define and execute the product roadmap for Agentic AI aligning with company strategy and customer needs. Partner with Engineering and Data teams to scale services powering large-scale AI workloads. Translate complex data and usage patterns into clear business insights and KPIs for customers and internal stakeholders. Coach and mentor the team and own their impact. Work closely with GTM and customer teams to drive customer value.

Undisclosed

()

Noida, India
Maybe global
Hybrid

Senior AI Product Manager, Product SKUs

New
Top rated
webAI
Full-time
Full-time
Posted

Lead the Product SKUs vertical by transforming custom field work into a robust, versioned, and standardized product library. Convert proven field implementations into repeatable SKUs and manage their lifecycle to ensure high reuse rather than a sprawling catalog of custom fixes. Define the SKU taxonomy by categorizing products based on use-case intent, constraints, and required outputs rather than just technology labels. Build evaluation harnesses including datasets, labeling standards, metrics, thresholds, and regression suites to establish the definition of done for each SKU. Enable sales teams by creating documentation and reference implementations to help Business Development recommend the right solutions for specific customer constraints. Oversee the versioning, deprecation, and discipline to avoid proliferating SKUs with minor differentiation.

Undisclosed

()

Austin, United States
Maybe global
Onsite

Senior AI Product Manager, Customer Engagement

New
Top rated
webAI
Full-time
Full-time
Posted

The Senior AI Product Manager is responsible for leading the discovery process to produce a Problem Brief for every customer engagement, including defining the job-to-be-done, constraints, success criteria, and reliability expectations. They define Evaluation Contracts that specify data, metrics, and thresholds for success before any building begins. The role includes partnering with AI Engineers to determine the appropriate technical approach such as Prompt Engineering, RAG, or Fine-tuning by debating trade-offs based on data, cost, and latency. The manager also identifies patterns in customer needs to surface platform gaps early and converts field learnings into engineering requirements. They focus on reducing ambiguity to enable AI engineers to execute immediately without requirement churn. Additionally, they synthesize market patterns across multiple customer deployments to identify strategic platform gaps and propose architectural improvements to the core platform based on field evidence.

Undisclosed

()

Austin, United States
Maybe global
Onsite

Global Mobility and Benefits Specialist

New
Top rated
Glean Work
Full-time
Full-time
Posted

The AI Outcomes Manager will partner with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on Glean. They will lead strategic reviews and advise customers on their AI roadmap to maximize value from Glean's platform. The role involves translating business needs into clear problem statements, success metrics, and practical AI solutions, while collaborating with Product and R&D to shape priorities. Responsibilities include conducting discovery workshops, scoping pilots, guiding rollouts to drive adoption, designing and building AI agents with and for customers, and rethinking and redesigning underlying business processes to enhance impact and usability. The manager will also proactively identify expansion opportunities and drive engagement across teams and functions.

$130,000 – $200,000
Undisclosed
YEAR

(USD)

United States
Maybe global
Remote

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Frequently Asked Questions

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[{"question":"What does an AI Product Manager do?","answer":"AI Product Managers oversee the planning and delivery of AI products that align with business goals. They define product vision, create roadmaps, and prioritize features throughout the product lifecycle. They collaborate with engineers, data scientists, designers, and stakeholders while conducting market research and competitive analysis. Beyond traditional PM responsibilities, they manage AI-specific tasks like running model evaluations, handling ethics concerns, addressing bias issues, and ensuring regulatory compliance. They monitor product performance, iterate based on user feedback, develop go-to-market strategies, and maintain documentation. Most importantly, they bridge technical and business gaps by translating complex AI capabilities into user-friendly products."},{"question":"What skills are required for AI Product Manager jobs?","answer":"AI Product Managers need a blend of technical and business skills. Technical competencies include understanding AI/ML fundamentals, model evaluation methods, and data analysis techniques. They should grasp NLP, computer vision, and generative AI concepts without necessarily coding them. Business skills involve strategic thinking, roadmap development, and prioritization frameworks. Communication is crucial for explaining complex AI concepts to non-technical stakeholders and translating business needs to technical teams. Project management abilities help coordinate cross-functional teams. Product discovery and user experience design skills ensure AI solutions solve real problems. Finally, ethical reasoning is essential for addressing AI bias, privacy concerns, and responsible implementation."},{"question":"What qualifications are needed for AI Product Manager jobs?","answer":"Most AI Product Manager positions require a bachelor's degree in computer science, engineering, business, or related fields, with many employers preferring master's degrees. Typically, 3-5 years of product management experience is expected, with demonstrable involvement in AI/ML products. Technical qualifications include understanding AI fundamentals, data structures, and evaluation metrics without necessarily having deep coding expertise. Professional certifications in product management (e.g., AIPMM) or AI/ML (from cloud providers) can strengthen qualifications. Employers value candidates who have shipped successful AI products, led cross-functional teams, and demonstrated ability to translate between technical and business stakeholders."},{"question":"What is the salary range for AI Product Manager jobs?","answer":"AI Product Manager salaries vary based on several factors including location, company size, industry, and experience level. Major tech hubs like San Francisco, New York, and Seattle typically offer higher compensation. Experience with specific AI domains (NLP, computer vision, recommendation systems) can command premium pay. Compensation also scales with responsibility – those managing enterprise AI platforms often earn more than those handling feature-level AI implementation. Education level, particularly advanced degrees in computer science or AI, can influence salary. Total compensation packages frequently include base salary, bonuses, equity, and benefits. Junior roles start lower while senior and director positions managing AI product portfolios reach the upper range."},{"question":"How long does it take to get hired as an AI Product Manager?","answer":"The hiring process for AI Product Manager roles typically takes 4-8 weeks from application to offer. The journey usually begins with a resume screening, followed by an initial HR call to assess fit. Technical screening often includes questions about AI concepts, product cases, and previous experience with machine learning products. Candidates then face 3-5 rounds of interviews with product leaders, engineers, data scientists, and executives. Many companies include a take-home assignment requiring candidates to define an AI product strategy or evaluate an existing AI feature. The specialized nature of these roles means companies often take longer to find candidates who demonstrate both product expertise and sufficient AI knowledge."},{"question":"Are AI Product Manager jobs in demand?","answer":"AI Product Manager jobs are experiencing strong demand as organizations increasingly incorporate AI into their products and services. Companies across industries are creating dedicated roles specifically for managing AI product development rather than simply expanding traditional PM responsibilities. This specialization reflects the unique challenges of AI products: evaluation methods, ethical considerations, and technical constraints differ from conventional software. Organizations seek professionals who can bridge the gap between business strategy and AI execution to drive revenue and operational efficiencies. The role is particularly sought after in technology, finance, healthcare, and retail sectors where AI adoption is accelerating. Recruiters now regularly post job descriptions specifically tailored to AI product management expertise."},{"question":"What is the difference between AI Product Manager and Traditional Product Manager?","answer":"AI Product Managers differ from Traditional Product Managers in several key ways. They require deeper technical knowledge of machine learning concepts, model evaluation methods, and data requirements without necessarily coding. Their development cycles include model training and testing phases beyond standard software development. AI PMs must address unique ethical considerations like bias, explainability, and privacy implications. They work extensively with data scientists and ML engineers, not just software developers. Success metrics often include model accuracy and confidence scores alongside typical product KPIs. Traditional PMs focus on feature functionality and user experience, while AI PMs must also consider model limitations, data quality issues, and the probabilistic nature of AI outputs."}]