Senior Product Manager | Applied AI

We are growing a product-management team that runs AI-powered products and applies AI across the whole product lifecycle. As a Senior Product Manager | Applied AI, you will own the vision, strategy, roadmap and delivery of one or more products — at least one of them AI-powered — while using AI day-to-day to work faster and make sharper decisions and mentoring other Product Managers as you do.
What "Applied AI" means here. This is a product role, not an engineering role. We expect confident, practical command of AI as a product manager — using it across the lifecycle and shaping AI-powered features — not the ability to build, train or tune machine-learning models as an ML engineer or data scientist would.
Req# 1100335863
The recruiting efforts for this position are intended to fill an existing vacancy for a new position.
Responsibilities
Own the vision, strategy, roadmap and end-to-end delivery of one or more products, including at least one that is AI-powered
Define requirements and use cases for AI features, treating them as probabilistic products — scoping data and use-case fit, and setting evaluation criteria, quality bars, guardrails and human-in-the-loop review as acceptance criteria
Identify where AI can improve the product, the customer experience, internal processes or business outcomes — and build and size the case for it
Use AI tools productively and with discipline across discovery, research synthesis, analysis, documentation, user stories, prototyping and planning — verifying outputs before relying on them
Prioritise features, own the backlog and manage release cycles, using AI-assisted analysis to support (not replace) your decisions
Manage the full product lifecycle, including the added considerations of AI features — model/version changes, quality drift and human oversight
Work closely with engineering, data, design and AI/ML teams, translating product intent into requirements they can act on and their constraints into product decisions
Set realistic expectations with clients and stakeholders about what AI can and cannot do, and communicate benefits, limitations and risks in plain language
Mentor Product Managers and raise the team's practical AI capability by example
Requirements
5+ years in Product Management, having managed one or more products end-to-end, including post-launch maintenance and support
Launched more than one product (or key capability) to market, with at least one experience delivering or materially improving an AI-powered product or feature (e.g., GenAI, ML, recommendations, search or automation)
Solid ownership of product strategy, vision and roadmap; market analysis and product visioning — including identifying and justifying where AI adds value
Experience owning backlogs, cross-product dependencies and release cycles, and managing product lifecycle and support models
Familiarity with product profitability, competitive positioning and pricing — including the cost, latency and quality trade-offs that shape AI-feature economics
Expertise across multiple (3+) business domains, able to act as a business-domain SME
Working AI literacy — what current AI (including GenAI/LLMs) can and cannot do reliably, common patterns and typical failure modes — enough to make sound product decisions and hold credible conversations with technical teams. Deep model-building knowledge is not required
Able to influence stakeholders up to and including VP level, and to lead all critical aspects of a product launch
Able to lead a team of Product Owners and/or Product Managers across a product line or family, guiding them through the full lifecycle
Raises the team's practical AI proficiency — sharing verified ways of working and coaching on requirements and evaluation criteria for AI features
Practical, daily use of AI across research, discovery, analysis, documentation, user stories, prototyping and planning — with verification of outputs
Ability to identify and justify AI opportunities in products, processes, CX and business outcomes
Working AI literacy — concepts, terminology, capabilities and limitations at PM depth
Experience defining requirements and use cases for AI features, including evaluation criteria, quality bars, guardrails and human oversight
Ability to evaluate AI outputs for quality, accuracy, risk, limitations and user impact
Responsible-AI awareness — privacy, bias, security, transparency and human oversight
Ability to work effectively with engineering, data, design and AI/ML teams
Adaptability and continuous learning as AI tools and capabilities evolve
Nice to have
Hands-on prototyping with AI builder tools to near-production fidelity
Building PM agents / multi-step automations across research, backlog, analytics and comms
Understanding of AI-feature economics (cost, latency, unit economics) and model lifecycle (drift, versioning, vendor change)
Familiarity with AI regulation (e.g., EU AI Act) and relevant sector rules
Prior experience taking an AI-powered product to production at scale
We offer
Extended Healthcare with Prescription Drugs, Dental and Vision, and Healthcare Spending Account (Company Paid)
Life and AD&D Insurance (Company Paid)
Employee Assistance Program (Company Paid)
Telehealth (Company Paid)
Short-term Disability (Company Paid)
Long-Term Disability
Paid Time Off (including vacation and sick days)
Registered Retirement Savings Plan (RRSP) with Company match
Maternity/Parental/Adoption Leave Top-up
Employee Stock Purchase Program
Critical Illness Insurance
Employee Discounts
Unlimited access to LinkedIn learning solutions
An artificial intelligence system is software that is developed with one or more techniques that can, for a given set of human-defined objectives, using algorithmic information processing, generate outputs such as content, predictions, recommendations, or decisions with varying levels of autonomy (“AI”). Tasks that humans have traditionally done by thinking and reasoning are increasingly being done by, or with the help of, AI to help create efficiencies.EPAM may use AI during the recruitment process, in connection with collecting or processing your personal data. Some (non-exhaustive) examples of tasks that EPAM may use AI for include conducting initial screening, creating transcripts of interviews, and assessing applications/CVs against defined job description criteria to make suggestions to the individuals evaluating your candidacy.Your personal data and the results of any processing are not shared with AI applications outside of EPAM infrastructure. While EPAM may use AI to help create efficiencies during the recruitment process, EPAM does not use AI to make hiring decisions, which is done by EPAM Talent Acquisition and management.
EPAM Canada welcomes and encourages applications from candidates with disabilities. Please contact WFA Human Resource CA WFAHRCA@epam.com if you have questions in this regard, or if you require an accommodation to complete the application process. Click here to review EPAM’s Accessibility for Ontarians with Disabilities Accessibility Policies and Multi-Year Access.
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our clients, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
Engineer the Future with a Career at EPAM

Work arrangement
Yes