Role Overview
We are seeking a Product Owner with experience in leading requirements and defining vision for GenAI, Machine Learning, and data-driven product development. In this role, you will define the vision, roadmap, and execution strategy for AI-powered products that transform customer experiences and operational efficiency. You will work closely with engineering, data science, UX, and business stakeholders to deliver scalable, high-impact AI capabilities.
Key Responsibilities
- Own the end-to-end product lifecycle for GenAI and AI/ML initiatives—from ideation to launch and continuous improvement.
- Define and communicate a clear product vision, strategy, and roadmap aligned with business goals.
- Translate complex AI/ML concepts into actionable requirements, user stories, and acceptance criteria.
- Partners with Data scientists and ML engineers to shape model development, evaluation, and deployment.
- Prioritize the product backlog based on customer value, feasibility, and business impact.
- Drive experimentation, POCs, and rapid prototyping for GenAI use cases (LLMs, RAG, copilots, automation).
- Ensure responsible AI practices, including model governance, data privacy, and ethical considerations.
- Collaborate with UX to design intuitive AI-powered user experiences.
- Track product performance using data-driven KPIs and iterate based on insights.
- Communicate progress, risks, and outcomes to executive stakeholders.
Required Qualifications
- 5+ years of experience as a Product Owner or Product Manager, with at least 1+ years in AI/ML or GenAI products.
- Strong understanding of LLMs, prompt engineering, RAG architectures, vector databases, model evaluation, and ML lifecycle.
- Experience working with cross-functional teams in agile environments.
- Ability to translate technical AI concepts into business value and user-centric features.
- Proven track record of launching AI-powered products at scale.
- Excellent communication, prioritization, and stakeholder-management skills.
Preferred Qualifications
- Familiarity with cloud platforms and MLOps frameworks.
- Familiarity with data engineering pipelines, feature stores, and model monitoring.
- Familiarity in NLP, computer vision, or predictive analytics.
- Experience integrating GenAI into enterprise workflows (chatbots, copilots, automation, content generation).
- Certifications in Product Ownership, Agile, or AI/ML