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Technical Product Owner (AI & Agentic Systems)

TripArc
Toronto, CAN
Full Time
Mid
Hybrid
2 weeks ago
Product OwnershipLLM FundamentalsRAG PipelinesAgentic SystemsBacklog ManagementScrum
Free

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Product OwnershipLLM FundamentalsRAG Pipelines
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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.
  • 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.

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

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

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

Compensation

  • The expected compensation range for this position is $110,000 to $130,000.

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