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Asensean Advisory

Principal Product Manager

Remote, Canada

Remote

$150,000 to $190,000 CAD / year · Full-time

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Applications open in a new tab.

Job details

Pay: $150,000 to $190,000 CAD / year
Job type: Full-time
Workplace: Remote
Experience: 8+ years of product management experience, including end-to-end ownership of B2B SaaS products or platforms and leadership across multiple products, initiatives, or teams.
Posting language: English
Posted: Oct 9, 2026

Original job description

Principal Product Manager

Company: Research Engineering Design Canada, Inc ('Redcan')

Location: Remote within Canada, ideally in the Greater Toronto Area, Kitchener-Waterloo, or Vancouver, British Columbia, to support occasional in-person collaboration.

Travel: Travel is regularly expected up to 25% of the time for customer engagements, industry events, and team collaboration, according to business needs.

About Redcan and the Role

Redcan builds agentic AI solutions leveraging the enterprise platforms its clients already use including solutions that make enterprise software faster to migrate and configure. The value comes from vertical applications built around existing data, workflows, and rules while people stay on the loop to step in where judgment matters.

We are seeking a Principal Product Manager to lead product strategy and execution across multiple products and initiatives. You will own customer problems and product outcomes from discovery through launch and adoption, balancing priorities, dependencies, and team capacity across the portfolio. Working with a small, experienced team of engineers and designers, you will turn opportunities into validated products and coordinate delivery across teams. You will engage directly with customers and collaborate with portfolio companies in the VC and PE ecosystem. This role calls for an entrepreneurial approach, practical AI proficiency, and the initiative to take on unfamiliar problems and move work forward with sound judgment.

Key Responsibilities and Outcomes

Customer and Market Insight

Lead continuous discovery across products with customers, developers, and business users, including public-sector and regulated-industry teams. Turn interviews, workshops, usability sessions, and usage data into clear problem statements.
Identify workflows where AI can deliver measurable value, such as case triage, routing, document search, and work order drafting. Validate demand and feasibility before committing delivery capacity.
Track customer needs, competitors, agent frameworks, model providers, and relevant policy and regulatory developments. Assess their implications across the product portfolio.
Anticipate market shifts and identify opportunities for new products or capabilities. Test assumptions early and use evidence to recommend where to invest.

Outcome: Product priorities reflect validated customer problems and change when new evidence warrants it.

Product Mastery and Solution Fit

Develop enough hands-on knowledge across the products you lead to run demonstrations, configure pilots, and build working prototypes with limited engineering support. Understand where existing capabilities meet customer needs and where investment is required.
Define requirements for AI-enabled products and workflows, including tasks, agent roles, permissions, human review, audit trails, and feedback loops.
Guide reusable capabilities and developer tooling where they improve delivery across products. Balance shared standards with the needs of individual customers and markets.
Partner with engineering on architecture decisions that affect security, privacy, tenancy, reliability, or auditability. Identify scale and edge-case risks early and agree on mitigations.

Outcome: Products solve the intended problems, and AI capabilities are bounded, reviewable, and reliable in use.

Product Strategy and Roadmapping

Own product strategies and coordinated 6 to 12 month roadmaps across multiple products and projects. Prioritize investment and sequence work against customer value, business objectives, dependencies, delivery capacity, and risk.
Lead build, buy, hybrid, and sunset recommendations, supported by customer evidence, cost, expected return, and the alternatives considered.
Decide which capabilities should be shared across products and which should remain product-specific, considering reuse, delivery speed, quality, and maintenance cost.
Set longer-term direction and contingency plans for model and vendor dependencies, data residency, and procurement constraints. Help shape positioning, go-to-market plans, and pricing for new products.

Outcome: Teams have clear product direction and an achievable sequence of priorities tied to customer and business outcomes.

Execution and Performance

Define and report product success measures, including adoption, customer outcomes, time to value, delivery speed, quality, AI performance, and operating cost.
Design experiments and comparisons with clear success criteria. Use the results to guide investment and improve products after launch.
Write product requirements with measurable outcomes. Coordinate execution across engineering, design, and other stakeholders, with clear ownership, milestones, dependencies, and release readiness. Manage scope and lead user acceptance testing and launch preparation.
Track risks, blockers, and changes across concurrent initiatives. Resolve issues promptly and escalate material trade-offs before they affect customer commitments.
Partner with engineering and business leaders on capacity planning and return-on-investment assessments across teams. Make priorities and resource constraints explicit, and adjust plans as conditions change.

Outcome: Teams deliver coordinated releases and measurable customer value, with clear accountability for progress, quality, and results.

Customer Engagement and Influence

Document decisions, trade-offs, and results in shared team materials, and revisit them against outcomes.
Present product direction and evidence to executives, engineers, portfolio companies, and customers, adjusting the depth and framing for each audience.
Align priorities across engineering, design, and business stakeholders. Facilitate decisions, resolve competing needs, and secure agreement on scope and expectations.
Lead customer discovery sessions, demonstrations, workshops, and pilot reviews. Translate feedback into actionable product decisions and communicate capabilities and delivery expectations clearly.
Build collaboration across teams and external partners, and represent Redcan products in business reviews and the wider OpenText Ventures ecosystem.

Outcome: Customers and stakeholders understand what we are building, why it matters, and what it will take to deliver.

Leadership and Initiative

Mentor product managers, co-ops, and designers, including coaching on discovery, product requirements, and evidence-based decisions.
Support recruiting and onboarding using Redcan's competency rubrics.
Create reusable playbooks for product intake, discovery, requirements, launch, and value assessment that improve work across teams.
Take initiative to identify gaps, learn unfamiliar domains, and lead work beyond established responsibilities when needed. Exercise commercial judgment, collaborate with specialists, and model Redcan's culture of rigor, curiosity, and continuous improvement.

Outcome: Teams become more effective, new opportunities receive disciplined attention, and useful practices carry forward across projects.

Qualifications

Bachelor's degree in Computer Science, Engineering, Business, or equivalent education or work experience.
8+ years of product management experience, including end-to-end ownership of B2B SaaS products or platforms and leadership across multiple products, initiatives, or teams.
Experience shipping AI or LLM-powered features to production, with an understanding of quality evaluation, failure modes, and cost management.
Experience with developer platforms, enterprise software, or workflow and low-code products, including products that other teams build on.
Experience in government, the public sector, or regulated industries where auditability, privacy, and procurement shape product decisions.
Technical fluency to understand architecture documents, API specifications, and pull requests, and contribute effectively to design reviews.
Practical proficiency with AI tools in day-to-day product work, including prototyping, analysis, research synthesis, and specification writing. Able to evaluate outputs critically, protect sensitive information, and apply human judgment.
Demonstrated entrepreneurial initiative, ownership, and communication skills. Comfortable managing concurrent priorities, learning beyond existing expertise, and working directly with customers.
Authorized to work in Canada without sponsorship, with willingness and ability to undertake occasional, reasonable business travel.

Preferred Skills and Experience

Agentic AI, including tool use, Model Context Protocol (MCP), agent skills, multi-agent orchestration, human-on-the-loop review, and evaluation methods.
Workflow and case management, including workflow engines, state machines, approvals, service-level deadlines, and task assignment.
Enterprise SaaS foundations, including multi-tenancy, identity and role-based access control, audit logging, and data residency.
Hands-on prototyping with AI coding tools such as Claude Code or Cursor, or with AI design tools.
Canadian public-sector context, such as municipal services or access-to-information processes including ATIP and FIPPA/MFIPPA.
Experience with OpenText data platforms and the wider ecosystem, or with VC- or PE-backed portfolio companies.

Our Commitment to Inclusion

Redcan is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We are building products for a diverse world and are committed to building and fostering an environment where our employees feel included, valued, and heard. We strongly encourage applications from racialized people, people with disabilities, people from gender and sexually diverse communities and/or people with intersectional identities. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, provincial, or local laws in the regions we operate. This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, or internships.

We thank all applicants in advance for applying. Only individuals selected for interviews will be contacted.

Staffing Firms: We do not accept unsolicited submissions. All firms must have valid agreements in place before any search engagements are considered.

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More about this job

Responsibilities

The Principal Product Manager will lead product strategy and execution across multiple AI-enabled products, owning the lifecycle from discovery through launch. They will collaborate with engineering and design teams while engaging directly with customers to validate problems and deliver measurable value.

Requirements

Candidates must have 8+ years of product management experience, specifically with B2B SaaS and AI or LLM-powered features. A bachelor's degree in a relevant field and the ability to work in Canada without sponsorship are required.

Skills

Product strategy
Agentic AI
B2B SaaS
Product management
Stakeholder management
Roadmapping
Customer discovery
Technical architecture
Workflow automation
Data analysis
Prototyping
Leadership
Mentorship
Market research
Regulatory compliance
Enterprise software

Benefits

4 weeks of vacation
10 wellbeing days
Fully-paid benefits

Remote locations

Toronto, Ontario, Canada
Kitchener-Waterloo, Ontario, Canada
Vancouver, British Columbia, Canada

Remote locations (standardized)

Kitchener, Ontario, Canada
Toronto, Ontario, Canada
Vancouver, British Columbia, Canada

Visa sponsorship

Not detected in the job text

Keywords

Principal Product Manager
Agentic AI
B2B SaaS
Product Strategy
Roadmapping
Customer Discovery
LLM
Enterprise Software
Workflow Automation
Low-code
API
Architecture
User Acceptance Testing
Go-to-market
Data Residency
Auditability
Privacy
Public Sector
Regulated Industry
Claude Code
Cursor
Model Context Protocol
Multi-agent orchestration
Product Lifecycle
Stakeholder Alignment
Mentorship
Commercial Judgment
Prototyping
Technical Fluency
Entrepreneurial Initiative

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