AI Product Owner I Remote

Key Responsibilities: · Value & Problem Definition: Identify high-impact use cases where AI/ML adds genuine user value rather than implementing AI just because it is trendy. · Data & Model Collaboration: Partner closely with data scientists, ML engineers, and data analysts to define dataset requirements, cleanliness, labeling, and accuracy thresholds. · Backlog Management & Prioritization: Structure Agile backlogs to accommodate iterative experimentation, raw data collection, model training, validation, and fallback logic. · User Stories & Acceptance Criteria: Translate complex AI capabilities (such as LLMs, RAG, or agentic workflows) into clear, INVEST-compliant user stories, test cases, and Gherkin-style acceptance criteria. · Responsible AI & Governance: Ensure compliance with data privacy regulations and AI frameworks (e.g., GDPR, EU AI Act) by auditing for bias, transparency, and human-in-the-loop safeguards. · Performance Monitoring: Track post-launch model drift, user adEligible to workion, accuracy metrics, and business ROI

Artificial Intelligence (AI), Artificial Intelligence (AI), Data Science, Agile Programming Methodologies, Establish Priorities, Machine Learning, Maintain Compliance, Data Collection, Training Data Sets, Auditing, Required Skills: · AI/ML Acumen: Familiarity with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, or predictive modeling (basic data literacy like SQL or Python is often preferred). · AI-Augmented Workflow: Experience using AI tools (such as Claude, ChatGPT, Azure AI, or agentic frameworks) to draft user stories, simulate edge cases, and run pre-mortem/what-if analyses. · Stakeholder Management: Ability to translate dense technical architecture into business outcomes for leadership, and business constraints into clear guidance for engineers

Preferred Qualifications: · Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related business field. · Experience: 5+ years in product management, software development, management consulting, or data analytics, with direct exposure to AI/ML products.

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