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Added 3 hours ago
Part Time Sales Manager
Michaels Stores
Leduc, AB
Part-time
Store - LEDUC, ABThe Sales Manager leads and champions a high-performing selling culture across the store, driving strong sales results and an engaging customer experience. This role…
Added 7 hours ago
Marketing & Communications Coordinator / Coordonnateur(trice), marketing et communications
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Remote, Canada
Full-time · Remote
Reports to: Marketing & Communications Manager
Added 2 days ago
Merchandise Manager
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Saskatoon, SK
Part-time
Store - SASKATOON, SKThe Merchandise Manager drives merchandising and operational execution, including truck processing, inventory routines, planogram sets, and visual standards. This role…
Added 2 days ago
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Full-time
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Added 13 days ago
Associate Product Manager - Co-op Student
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Toronto, ON
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Added 2 days ago
Engineering Manager, Forward Deployed Engineering (LLM)
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$260,000 to $380,000 USD / year
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Added 10 days ago
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Added 1 month ago
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Keep accurate daily reports and communicate progress to site supervisor or project manager
Added 2 days ago
Group Product Manager, AI & Data
Rightsline Inc
Toronto, ON
$190,000 to $205,000 CAD / year
Full-time
We are hiring a Group Product Manager, AI & Data to lead the execution of that arc. You will personally own and build our AI product line as the working PM – PRDs, prototypes, discovery,…
Added 3 days ago
Senior Manager, Marketing Innovation Strategist, Take-to-Market - Tangerine
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Added 4 days ago
Part Time Merchandise Manager. Must be available early mornings(3am, 5am & 7am), evenings and weekends
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Senior Manager, Marketing Innovation Strategist, Take-to-Market - Tangerine
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Added 3 days ago
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Added 3 days ago
Customer Experience Lead
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Sr. Product Manager, AICE - AI Center of Excellence
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Added 1 month ago
Maintenance Technician
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- General carpentry duties, framing, drywall etc.
Added 4 days ago
Project Executive
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Coordinate with Solutions Designers and the Manager of Construction Cost Estimating on
Added 4 days ago
Production Supervisor (Night Shift)
Stella-Jones
Neepawa, MB
Full-time
Places orders with the Production Manager or Manager, Plant Maintenance for any equipment or tools needed in the framing area

Rightsline Inc

Group Product Manager, AI & Data

Toronto, ON, Canada

Pay: $190,000 to $205,000 CAD / year
Job type: Full-time
Experience: 7–10 years of Product Management experience in B2B enterprise SaaS.
Posting language: English
Posted: Sep 18, 2026

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Original job description

This is a hybrid position out of our Toronto, Ontario office.

Overview

Rightsline is building the AI-native platform for IP commerce. We are moving from a modern system of record into an agentic product model. AI Assistants are in the market today, our first line of Agents coming next, and a longer arc that reshapes how our customers do the work of rights, royalties, and finance flows. Underneath the AI product line sits a modern analytics and reporting platform (Snowflake plus Sigma) that every product consumes.

We are hiring a Group Product Manager, AI & Data to lead the execution of that arc. You will personally own and build our AI product line as the working PM – PRDs, prototypes, discovery, and launches shipping on your own hands. Alongside that, you will directly manage Senior Product Manager(s) / Product Manager(s) and grow the AI & Data team as the Group's scope expands. You will set the craft bar for how we discover, build, evaluate, launch, and monetize AI products at Rightsline; make the build-vs-leverage-vs-partner calls across proprietary and third-party AI; and be the person the CPO and Executive Leadership Team look to for whether our AI bets are compounding into shipped customer value.

This is a player-coach product management role with a defined growth path as the Group scales and performs above expectations. The right candidate reads that path as motivating and the builder-first framing as freeing.

What You’ll Own

Build the AI Product Line – Hands-On

Personally own our AI product line as the working PM. You are the one running discovery, writing the PRDs, building the prototypes, and shipping new AI products into production.
Reimagine workflows in the world of AI: customer-back and future-first. We are not extrapolating today's product with AI sprinkled on. Fundamentally change how the work gets done, then design the surface.
Solve pain first. Every AI capability starts from a real, named customer job not from what a model can do. If we cannot describe the pain in a customer's own words, we do not build it.
Best-in-class, modern user experience. The AI surface is where our product feels different. Hold a top-tier UX bar with confidence indicators, human-in-the-loop patterns, exception handling, latency, and trust design as product properties.
Own the MCP integration surface both how our AI products consume model and tool contexts, and how Rightsline exposes its own capabilities as MCP services for external agents over time.
Own the AI product vision and multi-quarter roadmap for the Group. Translate the CPO's portfolio strategy into a sequenced, defensible plan and a board-approved agentic product vision.
Establish evals and telemetry / LLMOps as foundational not optional. Own the accuracy / trust / usability / cost tradeoff and be accountable when we get it wrong.
Guard the naming bar: functional names, no personas or marketing wrappers.

Cohesive AI Strategy – Proprietary + Third Party Partners

Own a coherent AI strategy across proprietary Rightsline capabilities and best-in-class third-party AI. The customer sees one product, one experience, one trust model not a patchwork of vendors.
Make explicit build-vs-leverage-vs-partner calls for every AI capability, and maintain an explicit "will not do" list.
Publish and maintain the Group's thesis on where AI creates compounding moats for Rightsline (proprietary data, workflow context, domain models).

Customer Discovery, JTBD & Design Partners

Run discovery on a Jobs to Be Done frame: map the user's full end-to-end role, not just the 30% that lives inside our product today. The 70% outside our product is the expansion opportunity.
Structured customer validation before scaling.
Bring customers along as design partners. Early Access Programs and co-design cadences are how AI capabilities graduate from prototype to GA not internal opinion.

Pricing, Packaging & Monetization

Own pricing, packaging, and monetization strategy for AI at Rightsline. Reason clearly across the modern set of AI monetization models like bundled features, add-on copilots, standalone AI products, and platform-plus-usage and match the model to the product shape.
Test pricing like a product launch. Beta cohorts, EAPs, preferential pricing during the pilot, then lock the model. Output-based, credit-based, and hybrid subscription-plus-usage are all on the table depending on the product shape.
PLG motion where it makes sense. Some AI surfaces may open a product-led entry point into Rightsline. You own identifying and running those bets when the shape fits.

Success Metrics & Financial Attribution

Own the AI product scorecard end-to-end including active adoption across the customer base, revenue attributed to AI capabilities, and customer value achieved.
Instrument every AI product for telemetry and LLMOps from day one. Financial attribution including expansion attached to AI, retention impact, ARR uplift as first-class product responsibility.

Manage Product Manager(s)

Personal build cadence is non-negotiable. PRDs, prototypes, and discovery cycles you personally run are part of the Group’s output – measured and reviewed alongside the ships your direct report(s) own. Personal ship is not optional; it is what makes the coach credible.
Directly manage a Senior Product Manager on day one. Set the Group’s craft standard: PRD quality, prototype rigor, launch discipline, and eval discipline. Every PM ships PRDs plus user stories plus working prototypes.
Build out the AI & Data PM team over time. As the AI product line matures and demands more PM coverage, you will hire additional PMs into the Group. Sequencing and shape are yours to propose to the CPO.

Cross-Pillar & GTM Partnership

AI is horizontal. Partner with Rights & Platform and Royalties & Financials PMs to embed Assistants and Agents where they compound the most. Never build in isolation, never let AI become a silo.
Work hand-in-glove with Engineering leadership on architecture, model selection, LLM-vs-deterministic tradeoffs, and integration surface area. Earn the room in technical discussions.
Partner with the CRO, Marketing, and Client Expansion on positioning, packaging, and landing AI capabilities. Sign off on Group launch claims for accuracy and defensibility.

What You’ll Bring

7–10 years of Product Management experience in B2B enterprise SaaS. Direct management experience is a plus but not the primary bar; the primary bar is having personally built and shipped AI products. Prior direct management of ICs is required as this seat manages a Senior Product Manager on day one. The primary weight in evaluation, however, sits on having personally built and shipped AI-native products; direct management experience alone, without shipped AI product, does not clear the bar.
Proven track record shipping AI-native products to production not AI features bolted onto existing workflows. You have personally taken at least one Agent-class product from zero to shipped, adopted, and measured.
Fluency with modern LLM application patterns including MCP servers, evals, prompt design, RAG, human-in-the-loop workflows, cost curve management, model selection, and telemetry / LLMOps.
Direct hands-on use of Claude, Codex, Cursor, or comparable AI development tooling in your own daily workflow.
Real experience running Jobs to Be Done discovery and translating it into product bets including structured interviews with power users, churned customers, and non-customers, not just the friendly voices.
Track record with pricing, packaging, and monetization for enterprise software, ideally including usage-based, credit-based, or hybrid subscription + usage models.
Comfortable at the seam between AI product surfaces and the reporting/analytics platform underneath. Prior experience shipping in an analytics, reporting, BI, or embedded data product area, cloud data warehouse plus embedded BI (Snowflake, Sigma, or comparable), is a strong plus.
Strong understanding of enterprise AI concerns like accuracy, explainability, permissions, data privacy, auditability, security, and customer trust treated as product properties, not compliance overhead.
Excellent written and verbal communication. You can frame an AI product strategy for the executive team and a sprint tradeoff for an engineer in the same afternoon.

How We’ll Know You Are the One

You are a builder first. Your happiest state is running discovery, writing PRDs, and shipping prototypes. Management is something you do to make more of that happen for the team around you.
You are AI-native, not AI-curious. You already reach for agents in your own daily workflow and have opinions about where AI improves decisions without weakening accountability or context.
You reimagine workflows customer-back. You do not sprinkle copilots onto existing UIs and call it AI.
You treat evals, trust, cost, and financial attribution as product properties. You can talk hallucination handling, confidence design, cost curves, and AI bookings definitions without notes.
You believe pricing and packaging are product work, not Finance work.
You see the seam between AI product surfaces and the reporting platform under them as a feature of the role, the two are stronger run together.

What We Offer

Significant impact: Direct influence over how the organization operates and executes
Executive visibility: Close partnership with C-suite leadership
Growth opportunity: Lead a team and shape operational strategy as we scale
Collaborative culture: Work with smart, ambitious cross-functional teams
Competitive compensation and benefits package

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More about this job

Responsibilities

You will personally own and build the AI product line by managing discovery, PRDs, and prototypes while leading a team of product managers. You will also define the AI strategy, manage pricing and monetization, and partner with cross-functional teams to ensure successful product launches.

Requirements

Candidates must have 7–10 years of B2B enterprise SaaS product management experience with a proven track record of shipping AI-native products. You must possess strong technical fluency in LLM application patterns and have direct experience managing individual contributors.

Skills

Product management
AI product development
Agentic product model
B2B enterprise SaaS
LLM application patterns
Jobs to be done
Pricing and monetization
Data analytics
Team leadership
PRD writing
Prototyping
Stakeholder management
Technical strategy
Customer discovery
LLMOps
Cross-functional leadership

Benefits

Competitive compensation
Significant impact
Executive visibility
Growth opportunity
Collaborative culture

Visa sponsorship

Not detected in the job text

Keywords

AI
Data
SaaS
Product Management
LLM
Snowflake
Sigma
MCP
RAG
Prompt design
Telemetry
LLMOps
Enterprise software
Pricing strategy
Monetization
Customer discovery
JTBD
Prototyping
PRD
Agentic product
Analytics
BI
Cloud data warehouse
Cross-functional
GTM
Strategy
Leadership
Product-led growth
User experience
Human-in-the-loop

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