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Added 2 mins ago
UI
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- $70,100 to $87,600 CAD / year
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Supra ITS

AI Product Owner

Mississauga, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Apr 25, 2027
Posting language: English
Posted: Oct 27, 2026

Original job description

SUPRA ITS

Managed IT | Cybersecurity | Cloud | BPO

AI Product Owner

Pumpkin AI Platform

Supra Canada Technologies Ltd.

Mississauga, Ontario

About Pumpkin AI

Pumpkin AI is an enterprise agentic AI platform built and operated by Supra ITS, part of the Canon group. The platform combines a library of specialist agents with a central control plane: admins create, entitle and deploy agents; end users work with them over documents, data, policy and operational systems.

Recent delivery includes a Dashboards agent, an eLearning agent that converts uploaded training material into video and audio learning content, and a no-code UI agent builder that lets non-developers assemble their own agents. Pumpkin AI runs in the cloud and on-prem, and is positioned to work alongside Microsoft Copilot and other enterprise AI stacks rather than against them.

The role

We are hiring an AI Product Owner to sit with the Pumpkin AI engineering team every day and own the backlog that turns platform capability into enterprise-ready product. You will be the single voice of the product for the squad: writing and ranking stories, defining acceptance criteria, accepting work, and holding the line on quality and compliance.

Your flagship mandate is the governance layer - the controls that make Pumpkin AI safe to sell into regulated, cost-conscious enterprises: spend and cost attribution, security and access control, no-code agent creation in the UI, privacy, and audit compliance. If governance is weak, enterprise deals stall. You own that outcome.

This is a hands-on Scrum Product Owner role, not a roadmap-only position. You will be in refinement, daily scrum, sprint review and retrospective with engineers, and you will be expected to reason about agent behaviour, tool calls, model routing and data boundaries well enough to make real trade-offs in the room.

What You Will Own

The Pumpkin AI product backlog: epics, stories, acceptance criteria, ranking and release scope, traceable from business outcome to merged code
The governance layer roadmap across cost, security, custom agent development in the UI, privacy and audit compliance
Agent lifecycle as a product surface: create, test in sandbox, entitle, deploy, monitor, retire
The no-code UI agent builder experience - what a non-developer can safely build, and what requires engineering
Definition of done for agent features, including evaluation criteria, failure modes and fail-closed behaviour
Stakeholder alignment across Supra ITS service delivery, security, client-facing teams and Canon group stakeholders
Release notes, demo narrative and the sandbox proof shown to clients and prospects before deployment

The governance layer: what good looks like

Cost: per-agent, per-tenant and per-user spend visibility, model and token attribution, budgets, quotas and alerting - no surprise invoices
Security: role-based access control, entitlements, secrets handling, tenant isolation, and agent permissions that are explicit and reviewable
Custom agent development in the UI: guardrails, approval workflow and promotion path so business users can build agents without creating shadow IT
Privacy: data residency, PII handling, retention and deletion, prompt and response redaction, and clear rules on what leaves the tenant boundary
Audit compliance: immutable logging of prompts, tool calls, data access and admin actions, with exports that satisfy SOC 2, ISO 27001 and client audit requests
Policy as product: controls that are configurable per client, not hard-coded, and demonstrable in a sandbox before a client signs

How You Will Work With The Team

Run the Scrum cadence with the engineering team: backlog refinement, sprint planning, daily scrum, sprint review and retrospective
Write stories with testable acceptance criteria; accept or reject work against them without negotiating the bar down at the end of a sprint
Partner with the Architect on ADRs so product decisions and technical decisions are recorded, not rediscovered
Work with QA on test coverage for agent behaviour, and with UX on admin and builder workflows
Keep a sandbox-first discipline: prove behaviour in Admin Sandbox before anything is entitled or deployed to a client
Balance client-driven requests against platform coherence - say no clearly, and explain the trade-off

Must-have Qualifications

Proven Product Owner experience in a Scrum team, working with engineers daily - backlog ownership, story writing, acceptance, release scope
Experience leading or owning the product for an Agentic AI team: agents, tool calling, retrieval, orchestration and evaluation in production, not pilots
Demonstrable work on an AI governance or platform control plane: cost controls, access control, privacy, logging and audit
Enough technical depth to debug a conversation with the team: you can read an agent trace, reason about a tool failure, and judge whether a control is real or cosmetic
Enterprise software judgment: multi-tenancy, entitlements, RBAC, and the difference between a demo and something a client auditor will accept
Clear written communication: stories, ADR input, release notes and executive updates that stand on their own
Comfort with ambiguity and with a platform that is still being shaped - you set direction rather than wait for it
[5+ years] product ownership or product management, including [2+] years on AI, data or platform products

Nice to have

Hands-on exposure to other agentic platforms: Google (Vertex AI / Agentspace), Microsoft (Copilot Studio, Azure AI Foundry) or AWS (Bedrock Agents) - strongly helpful
Experience positioning an AI platform alongside Microsoft Copilot rather than in competition with it
Background in regulated or audited environments: SOC 2, ISO 27001, GDPR, PIPEDA, HIPAA
Familiarity with RAG, vector stores, model gateways and spend attribution (LiteLLM-class routing)
MSP or managed services context: ticketing (ConnectWise-class), service delivery, client onboarding
Experience with no-code or low-code builder products and the support burden they create
Certified Scrum Product Owner (CSPO), PSPO or equivalent
On-prem and dual-cloud delivery experience (AWS / GCP / Azure, Docker, Kubernetes)

What This Role Is Not

A roadmap-and-slides role detached from the engineering team
A project manager role focused on status reporting rather than product decisions
A prompt-writing or AI-evangelist role without ownership of the backlog and the governance outcome
A Scrum Master role - we expect you to partner with one, not replace them

How We Work

Stories to ADRs to TDD implementation, review, then QA. Caps and fail-closed behaviour are product requirements, not engineering preferences. Every capability is proven in Admin Sandbox the same way a client will use it in production, and governance controls ship with the feature they govern - not in a later hardening sprint.

How To Apply

Send your resume and a short note on one agentic AI product you owned: what the agents did, how you governed cost and access, how you measured quality, and what you had to say no to.

Skills: ai governance,agentic ai platforms & autonomous ai agents,scrum,product ownership & product backlog management,ai evaluation & testing

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More about this job

Responsibilities

Own and prioritize the Pumpkin AI product backlog, define testable acceptance criteria, accept or reject completed work, and manage release scope in close collaboration with the engineering team. Lead the governance layer and agent lifecycle, including cost controls, security, privacy, auditability, no-code agent creation, and sandbox validation for enterprise clients.

Requirements

Requires 5+ years of product ownership or product management experience, including 2+ years working on AI, data, or platform products, with proven Scrum backlog ownership and production agentic AI experience. Candidates should have technical depth in agent behavior and governance controls, enterprise software judgment, and strong written communication; experience with regulated environments, agent platforms, and Scrum certifications is advantageous.

Skills

AI Governance
Agentic AI Platforms
Autonomous AI Agents
Scrum
Product Ownership
Product Backlog Management
AI Evaluation
AI Testing
Acceptance Criteria
Enterprise Software
Role-Based Access Control
Privacy and Audit Compliance
Cost Attribution
Multi-Tenancy
Stakeholder Alignment
No-Code Agent Building

Visa sponsorship

Not detected in the job text

Keywords

Pumpkin AI
Agentic AI
AI Governance
Product Ownership
Scrum
Product Backlog
Agent Orchestration
Tool Calling
Retrieval-Augmented Generation
AI Evaluation
Model Routing
Token Attribution
Role-Based Access Control
Multi-Tenancy
Entitlements
Data Residency
PII Handling
Audit Logging
SOC 2
ISO 27001
GDPR
PIPEDA
HIPAA
Microsoft Copilot
Copilot Studio
Azure AI Foundry
Google Vertex AI
AWS Bedrock Agents
Docker
Kubernetes

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