AI Product Owner

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 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,