In this role, you will define, deliver, and optimize AI products across platforms and diverse use cases. You will turn raw business opportunities into clear product roadmaps, balance complex technical trade-offs alongside ML engineers, and ensure every model delivers measurable, responsible ROI. The Tech Stack Deep-Dive Core Technologies & Frameworks AI / ML / GenAI Frameworks: Foundational knowledge in Generative AI, LLMs, and Machine Learning models. Cloud & Monitoring: Azure Monitor, Application Insights, or equivalent cloud ecosystem tools. Analytics & Business Intelligence: Power BI, Tableau, Qlik, or similar metrics tracking platforms. Must-Haves Solid experience in Agile product management, backlog prioritization, user story development, and SDLC practices. Hands-on experience with AI/data products, including data readiness, governance, and model evaluation (PoCs, A/B testing). Strong understanding of Responsible AI, privacy, ethical AI, and regulatory compliance frameworks. Proven business acumen: ability to build business cases, cost-benefit analyses, financial models, and pricing strategies (subscription, consumption, or outcome-based). AI/Cloud Certifications (e.g., Microsoft AI, Claude Associate, OpenAI, AWS, Google, or equivalent). Nice-to-Haves Bachelor's degree in CS, Data Science, Information Systems, or Engineering. Agile/Product Certifications (e.g., PSPO, CSPO, SAFe POPM, CBAP). Background in large-scale digital transformation or enterprise tech environments. Key Responsibilities (Keep it brief) Define Strategy & Requirements: Translate complex business needs into detailed Product Requirement Documents (PRDs), defining target baselines, fallback needs, and human-in-the-loop workflows. Guide Model & Tech Choices: Partner with Data Scientists and ML Engineers to evaluate model trade-offs involving quality, cost, latency, explainability, and security. Establish Evaluation & Telemetry: Build metric frameworks, baselines, and telemetry to track model accuracy, performance, cost per successful outcome, and adoption over time. Drive Responsible AI & Release: Lead governance, privacy, and compliance readiness while translating technical concepts clearly to executive stakeholders. Why Join Us? High Impact & Ownership: Own the full AI product lifecycle-from zero-to-one product discovery to operational scaling-with direct influence over architecture, pricing, and roadmap strategy. Collaborative Tech Culture: Work shoulder-to-shoulder with top-tier ML Engineers, Data Scientists, and Research Teams using modern AI capabilities. Enterprise Innovation: Drive tangible business outcomes and shape responsible AI practices at scale