Technical Product Owner (AI & Agentic Systems)

Founded in 2017, TripArc is a $750 million privately held company powers the top Travel Agencies and Tour Operators in North America. Our expansive and growing network empowers seamless access to a comprehensive range of travel options and services globally with over $750 million transactions annually - all at the industry’s best rates. As an industry leader in technology, purchasing, finance, HR and marketing, we know how to deliver solutions to travel professionals in the most effective way possible. With deep experience in partnering with two leading brands in the luxury travel space – Kensington Tours and Travel Edge –  TripArc has real insight into the needs of tour operators and travel agencies today. TripArc’s goals are simple. To make our network of over 1400 travel entities more profitable, efficient and help them create truly unique travel for their clients. This is a hybrid position with currently 2 days a week onsite from our office located at 2 Queen St. E in Toronto, ON. THE ROLE A Technical Product Owner for AI & Agentic Systems at TripArc maximizes product value by owning the delivery and continuous evolution of the company's internal LLM-powered and agentic platforms. They serve as the primary point of contact between travel advisor end-users, internal business stakeholders, and the development pod responsible for these systems, translating the capabilities and constraints of large language models, retrieval-augmented generation pipelines, and agentic frameworks into clearly defined backlog items. The Technical Product Owner is solely responsible for maintaining the Product Backlog at a pod level, using input from the Senior Product team, the development team, and direct end-user feedback to prioritize and communicate backlog items ahead of all Scrum ceremonies. They ensure the Product Backlog is visible, transparent, and understood at all times. Even where responsibilities such as technical ticket writing are delegated to a developer lead or architect, the Product Owner remains accountable for the outcome. Working within the Trifecta (Product, UX, Development) model, the Technical Product Owner maintains a deep understanding of AI system behaviour, output quality, and the advisor workflows these systems support. They anticipate the needs of stakeholders across the organization, including those not directly involved in day-to-day delivery, and ensure that all requests for backlog changes are evaluated and approved through them. KEY RESPONSIBILITIES Conduct needs assessments with end-users and internal stakeholders — including the Senior Product Manager, and business leadership — to identify requirements and translate them into features or user stories Develop and maintain a working understanding of the LLM architecture underpinning the platform, including retrieval-augmented generation (RAG) pipelines, prompt engineering patterns, tool/function calling, and agentic orchestration frameworks Define and maintain AI output quality standards; design and document evaluation criteria (e.g., response accuracy, latency, hallucination rates, retrieval relevance) to guide development and QA Collaborate with engineers and architects on decisions relating to model selection, context window management, embedding strategies, knowledge base curation, and agentic tool design Translate advisor workflows and domain-specific terminology — including travel industry concepts, supplier data structures, and booking logic — into structured system requirements that the development team can implement Create and manage the Product Backlog, including prioritization, grooming, and communication to the pod ahead of all Scrum ceremonies Identify gaps between the system's current capabilities and advisor needs; propose and scope solutions that leverage agentic patterns (multi-step reasoning, tool use, memory, search) appropriately Write acceptance criteria and user stories with sufficient precision to eliminate ambiguity for the development team, including edge cases related to AI response quality and failure modes Manage and coordinate beta programs for AI feature releases, including feedback collection, issue triage, and iteration planning Evaluate new AI tools, frameworks, and model releases independently; produce structured assessments against internal capability requirements Coordinate with the Solutions & Support team and other internal stakeholders to ensure AI system changes are understood, testable, and supportable Investigate and analyze problems, AI system behaviour, and user requirements in order to recommend appropriate solutions Prepare detailed flow charts and diagrams outlining system capabilities, agentic tool flows, and retrieval architectures Document system behaviour, design decisions, and known limitations for future reference Support the Senior Product Manager in the product roadmap process and long-term capability planning for AI-driven systems Prepare and facilitate planning and refinement ceremonies within the Scrum team KEY SKILLS / EXPERIENCE Bachelor's degree in Business, Information Science, Computer Science, or a related field; a combination of education and suitable work experience will be considered 3–5 years of experience in a Product Owner, Technical Business Analyst, or product role Comfortable reading REST API documentation, OpenAPI/Swagger specs, and data models Strong backlog management and prioritisation skills with experience facilitating Scrum ceremonies Demonstrated understanding of large language model fundamentals, including prompting strategies, context management, retrieval-augmented generation (RAG), and the behavioral characteristics and failure modes of generative AI systems Practical experience evaluating AI output quality, including defining evaluation metrics, designing test cases, and interpreting model responses for accuracy and relevance Familiarity with agentic system patterns, including tool/function calling, multi-step reasoning chains, and orchestration frameworks (e.g., n8n, LangChain, LlamaIndex, or equivalent) Experience producing structured requirements and specifications that engineering teams building AI systems can act on directly Ability to work fluently across both technical and non-technical stakeholders, translating AI system behaviour into plain language and business impact Skilled in structured business analysis on medium to large projects involving AI, data, or platform work NICE TO HAVE: Prior experience working on AI, ML, or LLM-powered products strongly preferred Familiarity with travel advisor workflows, travel industry terminology, or hospitality data models is an asset Experience with AI governance or shared AI configuration management is a meaningful differentiator CULTURAL FIT Thrives working in a technology and KPI-driven organization Able to thrive in an entrepreneurial environment Highly functional in a fast-paced, constantly changing workplace — building plans through iterations based on what is and is not working Ability to build trust and work through conflict both upwards and downward We know that our success is dependent on the people who join our team, which is why we recruit the best. Our team is made up of owners — people who are smart, low ego, and accountable for their results. We all play a part in the success of the company and are proud of what we do. COMPENSATION We provide a competitive compensation package with a strong pay-for-performance rewards approach. Employees have the opportunity to participate in incentive programs and compensation tied to business and individual performance. The expected compensation range for this position is: $110,000 to $130,000. The actual compensation may vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. #LI-Hybrid We are committed to providing employment accommodation in accordance with the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act. If you require accommodation due to a disability at any stage of our hiring process, please advise us when completing your application. The Range Group may use artificial intelligence throughout the recruitment process to screen, assess or select applicants for this position. These tools assist our hiring team but do not replace human judgment. Final hiring decisions are ultimately made by humans. We thank all candidates for their interest however only those selected for an interview will be contacted.

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