We are seeking a Senior Product Owner to drive the delivery of enterprise IT solutions while actively enabling AI-assisted and intelligent automation initiatives.
This role acts as the primary bridge between business stakeholders, IT delivery teams, and AI/data partners, ensuring solutions are well-defined, prioritized, governed, and aligned to business outcomes. The role spans traditional enterprise application delivery as well as emerging Copilot-style, AI-enabled, and agent-assisted workflows.
The ideal candidate combines strong business analysis and product ownership fundamentals with a practical understanding of how AI can augment decision-making, reduce manual effort, and modernize enterprise processes.
Responsibilities 1. Product Ownership & Enterprise Application Delivery
- Own and manage the product vision, roadmap, and backlog for assigned enterprise IT initiatives across business domains.
- Elicit and refine business requirements through workshops, interviews, and process reviews.
- Translate business needs into epics, features, user stories, and acceptance criteria using enterprise tools (e.g., Jira, Confluence).
- Document business processes, system flows, and functional logic using clear diagrams and narratives (e.g., Lucid).
- Assess enterprise systems end-to-end, from user experience through integrations, data flows, and downstream impacts.
- Balance business value, technical feasibility, regulatory obligations, and delivery risk.
- Support Agile, waterfall, and hybrid delivery models, including formal governance and design documentation where required.
- Write and execute functional test cases and support user and business acceptance testing.
2. AI & Intelligent Automation Opportunity Identification
- Analyze business processes to identify where AI, Copilot-style tools, automation, or agent-based solutions can reduce manual effort and improve outcomes.
- Identify repetitive, rules-based, or information-heavy activities suitable for AI augmentation or automation.
- Partner with stakeholders to frame AI opportunities in measurable business terms (e.g., productivity improvement, cycle time reduction, decision support).
- Leverage AI tools (e.g., Copilot, prompt-based assistants) to support requirements analysis, documentation, ideation, and early solution exploration.
- Identify decision points where AI can act as decision support or a semi-autonomous "digital teammate", with clear human oversight.
3. AI Requirements & Delivery Enablement
- Elicit and define requirements for AI-enabled initiatives, including:
- Business objectives and success criteria
- User interaction models (human-in-the-loop vs. automation)
- Inputs, outputs, decision boundaries, and escalation rules
- Translate business needs into AI-ready user stories, acceptance criteria, and prompt or logic descriptions suitable for AI or agent-based implementations.
- Identify and document data requirements for AI use cases (source systems, data quality, metadata, access constraints) in collaboration with SMEs and data teams.
- Work iteratively with technical and AI teams to validate feasibility, refine scope, and adjust requirements based on risk and complexity.
- Support testing and validation of AI outputs, including quality, accuracy, explainability, and exception handling.
4. AI Governance, Risk & Responsible Use
- Ensure AI-enabled features are appropriately governed, transparent, and aligned with enterprise AI, data, and security policies.
- Capture and maintain AI use-case documentation (purpose, scope, data inputs, user impacts, controls) to support governance and audit needs.
- Identify and factor in ethical, legal, data privacy, and compliance considerations when defining AI requirements.
- Collaborate with governance, legal, risk, and data teams to support AI approval, lifecycle management, and traceability.
5. Stakeholder Management & Change Enablement
- Serve as the primary point of contact between business, IT, vendors, and AI/data teams.
- Facilitate alignment on scope, priorities, risks, dependencies, and outcomes.
- Translate complex technical and AI concepts into clear, business-focused language.
- Support change management and adoption by clearly defining how AI-enabled capabilities fit into daily workflows and decision-making.
- Contribute to improving overall AI literacy through documentation, walkthroughs, and practical examples.
Qualifications- 4-6+ years of experience in Business Systems Analysis, Product Ownership, or IT delivery in an enterprise environment.
- Strong experience delivering enterprise applications using Agile, waterfall, or hybrid methodologies.
- Demonstrated experience writing clear requirements, user stories, process flows, and acceptance criteria.
- Practical, working knowledge of AI, automation, analytics, and Copilot-style tools (no model development required).
- Strong stakeholder management, communication, and facilitation skills.
- Hands-on experience with Jira, Confluence, and Lucid (r equired).
Preferred / Nice to Have
- Experience supporting AI-enabled, automation, or intelligent workflow initiatives.
- Familiarity with agent-based automation or advanced workflow orchestration concepts.
- Experience in domains such as automotive, finance, sales, contact center, or technical operations.
- Exposure to Kepner-Tregoe, Lean, Six Sigma, or process re-engineering methodologies.
- Relevant certifications (CSPO, SAFe POPM, PMP, or equivalent).
HIRING PRACTICES The salary range for this position is $94,750 - $112,516 annually. Individual salaries within this range are determined by a variety of job-related factors, including education, experience, knowledge, and skill set.
This is an on-site with occasional work-from-home position that requires employees to work on-site four days per week with the opportunity to work-from-home one day per week (with a dedicated workspace at the assigned company office).
This posting is for an existing vacancy that Honda Canada Inc. is actively seeking to fill.
