Technical Product Owner

Technical Product Owner – Ritchie Bros. Financial Services

RB Global is seeking a Technical Product Owner to help drive the delivery and continuous improvement of technology solutions supporting Ritchie Bros. Financial Services.

In this role, you will serve as a key connection between business stakeholders and technical delivery teams. You will translate business needs into clear requirements, user stories, acceptance criteria, and prioritized backlog items while helping guide work through design, development, testing, deployment, and production support.

The ideal candidate combines strong product ownership and Agile delivery experience with the technical knowledge to work effectively across software engineering, QA, integrations, APIs, enterprise systems, data flows, and data-focused teams.

This position is ideal for someone who enjoys solving complex business problems, improving processes, creating clarity across teams, and taking ownership from initial requirements through successful implementation and adoption.

WHY THIS ROLE MATTERS
•Influence how Financial Services product capabilities evolve by owning meaningful roadmap and backlog priorities.
•Translate business strategy into executable requirements, user stories, acceptance criteria, and sprint-ready work.
•Partner directly with business leaders, engineering, QA, system integrators, end users, and production support.
•Drive work across the full delivery lifecycle while balancing business value, technical feasibility, scope, and timing.
 

Key Responsibilities

• Own, maintain, and prioritize product roadmaps and backlogs based on business value, technical requirements, dependencies, and stakeholder priorities.
• Partner with business stakeholders to gather, analyze, and translate business needs into detailed requirements, user stories, acceptance criteria, and technical specifications.
• Lead backlog grooming, refinement, prioritization, sprint planning, and ongoing coordination with Agile delivery teams.
• Collaborate closely with software engineering, QA, integration, data engineering, data science, analytics, and other technical teams throughout the development lifecycle.
• Develop a working understanding of data science, machine learning, AI, and LLM-based solutions in order to effectively translate business objectives into actionable technical and product requirements.
• Partner with Data Scientists and technical teams to understand model inputs, outputs, data requirements, limitations, dependencies, and expected business outcomes.
• Support AI and LLM-enabled product capabilities by helping define use cases, business rules, prompt requirements, expected responses, evaluation criteria, and user experience requirements.
• Effectively communicate and refine prompts and business instructions for generative AI and LLM solutions, working with technical teams to improve accuracy, usability, and alignment with business needs.
• Support technical initiatives involving APIs, integrations, enterprise platforms, system interoperability, and data flows.
• Coordinate user acceptance testing, end-user reviews, defect resolution, deployment readiness, and production implementation.
• Identify opportunities to improve business processes, workflows, systems, and operating procedures.
• Develop and maintain clear documentation, process flows, SOPs, training materials, and implementation guidance.
• Support end-user communication, training, adoption, and transition to production.
• Monitor delivered capabilities, gather stakeholder feedback, and prioritize enhancements and continuous improvements.
• Communicate effectively with technical and nontechnical stakeholders and provide clear visibility into priorities, risks, dependencies, and delivery status.

Qualifications

• 3+ years of experience overseeing the design, development, implementation, or enhancement of software, systems, digital products, or technology capabilities.
• Demonstrated experience as a Technical Product Owner, Product Owner, Technical Business Analyst, Business Systems Analyst, or similar role.
• Hands-on experience managing product roadmaps, requirements, user stories, acceptance criteria, backlog grooming, prioritization, and sprint delivery.
• Strong understanding of Agile methodologies, Scrum practices, and the software development lifecycle (SDLC).
• Ability to translate complex business requirements into clear, actionable requirements for engineering, QA, integration, data engineering, and data science teams.
• Working knowledge of data science, machine learning, analytics, and AI concepts, with the ability to communicate effectively with Data Scientists and technical specialists.
• Familiarity with generative AI, large language models (LLMs), and prompt-based applications, including the ability to structure, communicate, test, and refine prompts and expected outputs for business use cases.
• Ability to understand data inputs, outputs, workflows, model requirements, and technical dependencies without needing to personally develop data science models.
• Experience working with APIs, system integrations, enterprise applications, technical requirements, and data flows.
• Experience coordinating UAT, implementation, deployment, documentation, training, and production support activities.
• Strong analytical, problem-solving, process-improvement, and organizational skills.
• Excellent written and verbal communication skills with the ability to bridge conversations between business stakeholders, product teams, engineers, and data science professionals.
• Ability to manage competing priorities and drive initiatives from concept through implementation.

Preferred Qualifications

• Experience within financial services, lending, equipment finance, payments, fintech, banking, or another regulated environment.
• Experience partnering directly with Data Scientists, machine learning teams, analytics teams, or AI-focused engineering teams.
• Exposure to LLMs, generative AI, prompt engineering, AI agents, or other emerging AI-enabled product capabilities.
• Understanding of how APIs, data pipelines, enterprise platforms, and AI/data science capabilities work together within a product ecosystem.
• Experience supporting complex enterprise systems and cross-functional technology implementations.