Sr. Product Owner, AI Authoring Systems
Role details
Job location
Tech stack
Job description
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Drive AI product strategy across the authoring ecosystem, identifying opportunities where AI can meaningfully accelerate content development, improve quality, and expand delivery capabilities.
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Create investment business cases supporting platform strategy, including, KPI definition, stakeholder approvals, buy/build/partner recommendations, and execution accountability.
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Conduct ongoing market and user research to deeply understand authoring team needs, content development challenges, and the competitive landscape for AI-powered authoring tools.
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Partner with business and product leadership to build an iterative development roadmap that delivers measurable customer value and drives revenue growth.
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Lead evaluation, selection, and management of AI technology partners and vendors, ensuring alignment with platform strategy, ethical AI principles, and cost optimization.
AI & Technical Implementation
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Lead strategy and implementation of AI-powered authoring features including intelligent content generation, adaptive recommendations, automated tagging and taxonomy, and quality assurance tooling.
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Collaborate with data science and engineering teams to develop and refine AI/ML models that enhance authoring workflows and improve content outcomes.
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Maintain strong working knowledge of LLM-powered product patterns (e.g., RAG, prompt orchestration, evaluation/guardrails) and common orchestration frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex) to define feasible, high-value features-without requiring hands-on engineering.
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Oversee ethical AI implementation-ensuring fairness, transparency, bias mitigation, and privacy across all AI-driven authoring features.
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Define and monitor AI-specific success metrics, including model performance, user adoption, content quality improvements, and ROI of AI investments.
Authoring Ecosystem Ownership
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Own the end-to-end product lifecycle for authoring systems-from conception and requirements through launch, iteration, and continuous improvement.
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Serve as the voice of the customer within the authoring ecosystem, representing production teams, SMEs, vendors, and instructional designers in all product decisions.
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Partner with technical and product leaders across the organization to align authoring platform investments with broader content strategy and delivery goals.
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Lead business acceptance testing (BAT), product training, and enablement for portfolio, marketing, and sales stakeholders.
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Partner with customer support and sales teams to troubleshoot authoring system pain points and drive continuous product improvements.
Cross-Functional & GTM Execution
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Align and influence cross-functional teams-Engineering, Data Science, UX, Production and Product Development, and Platform-around the AI-authoring product vision.
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Effectively communicate complex technical concepts and AI capabilities to senior leadership and non-technical stakeholders.
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Partner with content teams and business stakeholders on all aspects of the Go-to-Market Plan for new features, including data capture, release timelines, training, and internal/external communications.
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Measure and report on in-field product performance against KPIs; update internal stakeholders and adjust strategies as market conditions evolve.
Requirements
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Bachelor's degree, advanced degree preferred.
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5-7 years' experience in product management or related field with a focus on AI driven products and features.
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Strong working knowledge of LLM-powered product patterns and common orchestration frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex), with the ability to translate capabilities/constraints into requirements and tradeoffs; hands-on engineering experience is not required.
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Understanding of NLP, machine learning, and deep learning concepts as applied to LLM/GenAI systems (e.g., embeddings, retrieval, evaluation, and risk/quality tradeoffs).
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Knowledge of AI ethics, bias mitigation, and responsible AI development.
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Data-driven mentality with focus on analyzing and synthesizing ROI, usage, and/or research data to understand market trends and product performance to create data-informed strategies.
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Track record of successful AI product and/or feature launches.
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Experience managing and delivering multiple projects to deadline and budget simultaneously.
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Comfortable with ambiguity; adapts and pivots quickly in response to changing conditions.
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Thrives in a fast-paced, deadline-oriented environment.
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Professional experience with agile methodologies and processes.