Product Manager

An AI Product Owner (PO) bridges business goals, data science, and Agile engineering to define, prioritize, and deliver artificial intelligence and machine learning features

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 adoption, accuracy metrics, and business ROI

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.