Product Owner (AI-First)

Position Summary :
The Product Owner (AI-First) is responsible for defining product vision, managing backlog priorities, and ensuring the delivery of high-value product outcomes across web, mobile, and AI-enabled platforms. This role bridges business, technology, data, and user needs, with a strong focus on AI automation, LLM-based features, workflow orchestration, and scalable digital product development. The role is ideal for a technically strong Product Owner who can work effectively with engineering, AI/ML, and business stakeholders to translate strategic opportunities into production-ready features and measurable business value.
Key Responsibilities:
• Define and communicate the product vision, roadmap, and priorities to development teams and stakeholders, ensuring alignment with business goals and customer value.
• Build, refine, and manage the product backlog, including stories, epics, themes, acceptance criteria, and release planning to keep teams execution-ready.
• Assess business value, technical feasibility, delivery risk, and strategic fit to prioritize work that delivers the highest impact.
• Work closely with Engineering, AI/ML, Data, Design, and Product Management teams to shape product requirements and clarify trade-offs across scope, time, quality, and cost.
• Lead discovery and delivery for AI-first product capabilities such as LLM-powered assistants, agent workflows, automation features, retrieval-based systems, and reusable AI components.
• Collaborate with technical teams on AI solution patterns such as prompt design, RAG, orchestration, evaluation, model selection, latency management, and cost optimization.
• Define measurable success criteria for both product and AI performance, including user adoption, task success rate, automation rate, response quality, time-to-value, and operational efficiency.
• Research users, market trends, competitor offerings, and emerging technologies in AI, automation, SaaS, fintech when relevant to product direction.
• Support sprint execution by removing blockers, clarifying requirements, and helping teams maintain momentum toward sprint and release goals.
• Ensure responsible AI practices by partnering with security, legal, and compliance stakeholders on privacy, transparency, risk controls, and safe deployment standards.