> Markdown version of [/jobs/ext/3844389-ai-product-owner-i-remote](https://www.wearedevelopers.com/jobs/ext/3844389-ai-product-owner-i-remote). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Product Owner I Remote - **Company:** Diverse Lynx LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Training Data, Agile Methodology, Artificial Intelligence, Python (Programming Language), Machine Learning, Software Product Management, Raw Data, Software Engineering, SQL Databases, Retrieval-Augmented Generation, Large Language Models, Generative AI, Agentic-AI, Gherkin, Information Technology, Data Analytics, Performance Monitor, Claude, Azure AI, GPT - **Published:** October 20, 2026 - **Apply:** https://www.careerbuilder.com/job-details/ai-product-owner-i-remote-avenel-nj--fbfb5f4f-f7ff-4762-9d56-92bc1e65ddd6 ## About the Role 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. ## Description 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