AI Product Owner We are looking for a strategic, technically minded AI Product Owner to lead the vision, roadmap, and execution of AI-powered features within our SaaS platform. You will bridge the gap between business goals, customer needs, and data science/machine learning engineering teams. Your mission: deliver intelligent, scalable features that drive user value and business growth.Key ResponsibilitiesProduct Strategy & RoadmapDefine and maintain the AI product roadmap aligned with company OKRs, market trends, and customer feedback. Prioritize features that leverage machine learning, NLP, recommendation systems, or generative AI to solve real user problems.Backlog ManagementWrite clear, actionable user stories and acceptance criteria for AI features. Balance short-term delivery with long-term research and experimentation (e.g., A/B testing models, prompt engineering improvements).Cross-Functional CollaborationAct as the primary liaison between engineering, data science, design, marketing, and customer success. Translate technical model performance metrics (accuracy, latency, drift) into business impact statements for stakeholders.Data-Driven Decision MakingDefine success metrics for AI features (e.g., conversion lift, user engagement, automation rate). Use analytics and model evaluation results to iterate on features and prioritize improvements.Ethics & GovernanceEnsure AI features are fair, transparent, and compliant with data privacy regulations (GDPR, CCPA). Champion responsible AI practices across the product lifecycle.Customer & Market InsightsConduct user research, competitive analysis, and industry trend monitoring to identify new AI opportunities. Partner with customer success to validate hypotheses through prototypes and MVPs.Release & Lifecycle ManagementCoordinate beta programs, feature flags, and gradual rollouts for AI models. Monitor post-launch performance and manage continuous model retraining or fine-tuning cycles.QualificationsRequired7+ Years of experience.3+ years of product ownership/management experience in a SaaS company.Proven experience owning AI/ML features (recommendation engines, intelligent search, chatbots, predictive analytics, etc.).Strong understanding of ML lifecycle, model inference, evaluation metrics (precision/recall, AUC, RMSE), and trade-offs between accuracy and latency.Ability to write technical user stories and communicate with data scientists and engineers.Analytical mindset with experience using SQL, product analytics tools (Amplitude, Mixpanel, etc.), and A/B testing frameworks.Excellent stakeholder management and presentation skills.Nice-to-HaveBachelor’s or Master’s in Computer Science, Data Science, AI, or related field.Experience with generative AI (LLMs, RAG, prompt engineering) and vector databases.Familiarity with agile/scrum methodologies and tools like Jira, Confluence.