ITS Managed IT | Cybersecurity | Cloud | BPO
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 hand-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 explicit 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-tenant, 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.

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📌 AI Product Owner (Ontario)
🏢 Supra ITS
📍 Ontario