Technical Product Owner (AI & Agentic Systems)
About The Position
TripArc is seeking a Technical Product Owner for AI & Agentic Systems to maximize product value by owning the delivery and continuous evolution of the company's internal LLM-powered and agentic platforms. This role serves as the primary point of contact between travel advisor end-users, internal business stakeholders, and the development pod responsible for these systems. The Technical Product Owner will translate the capabilities and constraints of large language models, retrieval-augmented generation pipelines, and agentic frameworks into clearly defined backlog items. They will be solely responsible for maintaining the Product Backlog at a pod level, prioritizing and communicating backlog items ahead of all Scrum ceremonies, ensuring visibility, transparency, and understanding. The role requires a deep understanding of AI system behavior, output quality, and advisor workflows, anticipating stakeholder needs and managing all requests for backlog changes. This is a hybrid position with 2 days a week onsite at our Toronto office.
Requirements
- 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 prioritization 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 behavior into plain language and business impact.
- Skilled in structured business analysis on medium to large projects involving AI, data, or platform work.
Nice To Haves
- 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.
Responsibilities
- Conduct needs assessments with end-users and internal stakeholders to identify requirements and translate them into features or user stories.
- Develop and maintain a working understanding of the LLM architecture, including RAG pipelines, prompt engineering patterns, tool/function calling, and agentic orchestration frameworks.
- Define and maintain AI output quality standards and design evaluation criteria (e.g., response accuracy, latency, hallucination rates, retrieval relevance).
- 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 into structured system requirements.
- Create and manage the Product Backlog, including prioritization, grooming, and communication to the pod ahead of all Scrum ceremonies.
- Identify gaps between system capabilities and advisor needs; propose and scope solutions leveraging agentic patterns.
- Write acceptance criteria and user stories with sufficient precision, 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, producing structured assessments.
- 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 behavior, and user requirements to recommend appropriate solutions.
- Prepare detailed flow charts and diagrams outlining system capabilities, agentic tool flows, and retrieval architectures.
- Document system behavior, design decisions, and known limitations.
- 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.
Benefits
- Competitive compensation package
- Strong pay-for-performance rewards approach
- Opportunity to participate in incentive programs
- Compensation tied to business and individual performance
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
