• Led end-to-end ownership of AI-driven SaaS products, defining vision, roadmap, and success metrics aligned with enterprise customer needs.
• Prioritized features using data insights, customer feedback, and market research to balance technical feasibility and business value.
• Oversaw model monitoring and retraining processes to maintain accuracy, fairness, and compliance with ethical AI standards.
• Coordinated with legal and compliance teams to ensure responsible AI usage and data privacy adherence.
• Conducted stakeholder reviews and executive briefings to communicate progress, risks, and product impact.
• Implemented A/B testing frameworks to evaluate model performance and user experience improvements.
• Mentored associate product managers and established best practices for AI product documentation.
• Managed vendor partnerships for third-party AI tools and APIs to accelerate development timelines.

• Defined and launched AI-powered analytics products that enabled customers to automate decision-making workflows.
• Translated complex ML concepts into clear product requirements and user stories for engineering teams.
• Partnered with UX designers to create intuitive interfaces for data-heavy AI applications.
• Worked closely with data teams to define training data requirements and model evaluation criteria.
• Monitored product KPIs including model accuracy, latency, and user adoption rates.
• Led sprint planning and backlog grooming sessions to ensure timely delivery of AI features.
• Conducted customer interviews and usability testing to validate AI-driven features before release.
• Coordinated go-to-market strategies with sales and marketing teams for product launches.
• Reduced time-to-market by streamlining AI experimentation and prototyping workflows.

• Supported senior product managers in building AI-enabled enterprise tools for operations and forecasting.
• Assisted in defining MVP requirements for machine learning features based on customer pain points.
• Analyzed user data and feedback to identify opportunities for AI-driven enhancements.
• Worked with QA teams to validate model outputs and ensure reliability before production release.
• Documented product specifications, workflows, and model assumptions for internal stakeholders.
• Participated in sprint reviews and retrospectives to improve team efficiency and delivery quality.
• Coordinated with customer support teams to resolve AI-related product issues.
• Helped track product performance metrics and prepared reports for leadership reviews.

Contributed to the creation of internal guidelines for ethical AI usage and bias mitigation

Developed an AI-based forecasting product used by enterprise clients to reduce inventory costs

Led the design and launch of a personalized recommendation system that increased user engagement by 35%