Senior Product Manager (Applied AI) (Quebec City)

Senior Product Manager (Applied AI) (Quebec City)

12 Oct
|
Coursera
|
Quebec City

12 Oct

Coursera

Quebec City

We are looking for a Senior Product Manager, Applied AI to own customer deployments from initial discovery and product scoping through delivery, adoption, and value realization
In this role, you will work directly with enterprise customers to understand their most important workflows, translate business objectives into clear product and technical requirements, and build a sequenced deployment roadmap. You will partner closely with Forward Deployed Engineers, internal Product and Engineering teams, and cross-functional partners across Sales, Customer Success, Data, Security, Legal, Finance, and Operations
You will serve as the product owner for the customer engagement: accountable for the problem being solved, the scope and success criteria, the deployment roadmap, and the business value ultimately delivered. You will also help identify which customer needs represent repeatable product opportunities and work with the internal teams to incorporate those insights into the broader product roadmap
This is an opportunity to join an emerging motion at an early stage and requires people with entrepreneurial mindset. Beyond delivering individual customer engagements, you will help define the product, operating model, playbooks, and decision frameworks required to scale this recent product and motion
Build trusted relationships with customer executives, business leaders, technical stakeholders, and end users
Lead discovery to understand customer objectives, workflows, user needs, data and technical constraints, and desired business outcomes
Identify and prioritize high-value use cases, define the minimum viable deployment, and establish clear success and acceptance criteria
Translate ambiguous customer problems into clear product requirements, prioritization decisions, and a sequenced product and deployment roadmap
Translate customer objectives into a clear product and deployment roadmap covering milestones, workstreams, dependencies, risks, decision points, and launch criteria
Create high-quality product artifacts, including problem statements, product requirements, workflow definitions, user stories, acceptance criteria, prioritization frameworks, and executive decision documents
Own delivery governance across Coursera + Udemy and customer teams, maintaining clarity on scope, timelines, responsibilities, risks, and unresolved decisions
Work closely with Forward Deployed Engineers and internal Engineering teams to translate business workflows into deployable technical solutions
Participate credibly in discussions involving system architecture, APIs, data flows, integrations, identity and access management, infrastructure, security, privacy,



scalability, reliability, and deployment models
Evaluate technical and product trade-offs, challenge assumptions, and ensure that proposed solutions are feasible, supportable, secure, and aligned with customer outcomes
Partner with engineering teams on AI-specific considerations such as data quality, evaluation approaches, human oversight, model limitations, responsible AI, and production-readiness criteria
Define the value hypothesis for each customer engagement and establish the business, adoption, and product metrics required to measure success
Evaluate effort, implementation complexity, cost-to-serve, and expected customer value when making scope and prioritization decisions
Partner with Sales, Finance, Legal, and Customer Success on scope boundaries, business cases, commercial assumptions, and material changes to customer engagements
Translate deployment results into clear narratives on adoption, ROI, customer impact, and future opportunities
Identify recurring customer workflows, requirements, and technical patterns that can become reusable product capabilities
Partner with Product and Engineering teams to bring field insights into the broader roadmap and build repeatable discovery, scoping, deployment, and measurement playbooks
Benefits Coursera covers the cost of tuition so you can earn a free master’s degree and develop new skills. That’s on top of free, lifelong access to courses and certificates on the platform
We offer medical, dental, and vision insurance for you and your dependents. Plus, free access to counseling and mental health services
Get up to 16 weeks of fully-paid parental leave when you grow your family and bring a new child into your life
We host Make-a-thon events twice a year to promote community and innovation. During Make-a-thon, you’ll dedicate time to attend workshops, work on passion projects, and pursue ideas outside of your day-to-day work
Take paid time off when you need it. We have time off policies that promote flexibility so you can tailor your work schedule when life calls
Our flexibility extends to where you work. You can choose to work from home, work from one of our offices, or try a combination of the two
Employees earn company stock,



so you can own what we build together and share in our success
Experience Experience working with B2B products involving platforms, data, APIs, integrations, infrastructure, or complex enterprise workflows
Demonstrated experience taking technically complex enterprise products, platforms, or customer deployments from discovery and scoping through production launch and adoption
Strong technical fluency and the ability to reason about enterprise software architecture, data and integrations, cloud environments, security, privacy, and software delivery
Excellent product judgment with the ability to convert ambiguous problems into clear requirements, prioritized roadmaps, and measurable outcomes
Financial and commercial acumen, including experience evaluating business cases, effort versus value, delivery economics, ROI, and the implications of scope and prioritization decisions
Strong understanding of AI- and LLM-enabled products, including where these technologies create value, their limitations, and the considerations involved in deploying them in enterprise workflows
Willingness to collaborate across global time zones and travel periodically for customer discovery, delivery, and executive engagements
Strong program and delivery management skills, including managing multiple workstreams, dependencies, risks, changing scope, and executive-level communication
Hands-on prototyping experience with AI-assisted or low-code development tools such as Claude, Cursor, Lovable, Retool, or similar platforms
Ability to operate effectively in ambiguity, influence cross-functional teams without formal authority, and communicate equally well with executives, product teams, and engineers
Solid customer-facing experience working directly with senior business leaders, technical stakeholders, and executive sponsors
8+ years of relevant experience across B2B product management, enterprise software, technical consulting, solutions delivery, or related roles, with clear ownership of product or customer outcomes
Experience deploying AI, machine-learning, LLM, RAG, or agentic solutions into production enterprise environments
Familiarity with AI evaluation, guardrails, human-in-the-loop workflows, observability, model performance, and responsible-AI practices
Experience working in education technology, workforce transformation, talent intelligence, skills, learning platforms, or other enterprise environments involving complex stakeholder and data ecosystems
Experience delivering products or programs across multiple regions, industries, or regulatory environments

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📌 Senior Product Manager (Applied AI) (Quebec City)
🏢 Coursera
📍 Quebec City

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