What You Will Do:

• Drive AI-Powered Product Innovation
• Define product vision and roadmaps for client solutions leveraging GenAI, LLMs (GPT-4, Claude, Llama, Gemini), RAG architectures, and Agentic AI frameworks
• Lead end-to-end product lifecycle from ideation through launch for AI/ML products, ensuring alignment with client business objectives and KPIs
• Develop compelling business cases by analyzing market opportunities, competitive positioning, and ROI projections for AI implementations
• Lead Complex Data & Migration Initiatives
• Oversee product strategy for large-scale data migration projects across cloud platforms (AWS, Azure, GCP)
• Guide data product development including ingestion pipelines, transformation layers, governance frameworks, and consumption APIs
• Ensure data quality, security, compliance, and observability across all deliverables
• Champion Agile Delivery Excellence
• Facilitate Agile ceremonies and maintain well-groomed backlogs with properly sized, technically detailed features and epics
• Define sprint goals aligned with quarterly objectives and long-term product vision
• Balance technical debt management with feature delivery, advocating for architectural improvements
• Enable Cross-Functional Collaboration
• Partner with client stakeholders, engineering teams, data architects, ML engineers, and UX designers to deliver integrated solutions
• Translate technical capabilities into business value narratives tailored for different audiences, from developers to executive leadership
• Conduct design thinking workshops, user research sessions, and gap analyses to uncover insights and validate product direction.

Required Qualifications:

• 5 to 7+ years of experience in product management with demonstrated success taking technical products from 0 to 1 and scaling
• 3 to 5+ years of experience with AI/ML products, Generative AI, or data platform development
• 3 to 5+ years working in Agile/Scrum environments with strong command of Agile methodologies and ceremonies
• Deep understanding of cloud architectures (AWS, Azure, GCP) and the modern data stack
• Deep expertise in modern data architectures and platforms such as Snowflake, Databricks, and BigQuery
• Understanding of GenAI technologies: prompt engineering, fine-tuning, RAG, vector databases, and embedding models
• Experience with Agentic AI frameworks such as LangChain, AutoGPT, or CrewAI