• Help define product vision, strategy, roadmap, and growth opportunities, identifying areas of improvement. • Work hands-on with the development, design and customer-facing teams, participating in stand-ups, providing feedback, and assisting in testing. • Keep track of industry trends, diving into product and customer discovery. • Ensure new products and features are evaluated for usability and performance, employing focus group testing when necessary.

• Own the translation of raw alternative datasets into scalable, agent-ready data products. • Design methodologies that answer high-value business questions, determining how disparate datasets should be combined, normalized, and interpreted. • Partner closely with Data Engineering to shape source data pipelines into clean, well-structured datasets with clear definitions and documentation. • Develop deep expertise in the strengths, limitations, biases, and coverage characteristics of key datasets and ensure those nuances are reflected in downstream outputs. • Define how the Insight Agent should use different datasets, including valid query patterns, edge cases, failure modes, and methodological guardrails. • Own metric definitions, data lineage, and documentation to ensure the agent consistently delivers accurate and explainable answers. • Establish standards for how the agent reasons across multiple datasets, preventing over-interpretation and ensuring conclusions remain statistically defensible. • Serve as the final reviewer for methodology-related changes that impact agent behavior. • Translate customer questions into scalable methodologies, data models, and agent capabilities. • Expand the range of questions the agent can answer by enabling new forms of segmentation, cohort analysis, behavioral measurement, and cross-dataset insights. • Partner with Product, Engineering, and Leadership to identify new data sources, use cases, and capabilities that increase the commercial value of the Insight Agent. • Help shape the product roadmap by turning emerging customer needs and experimental insights into repeatable product functionality. • Coordinate testing and validation of staged data changes before they reach production. • Own incident management processes for data quality issues, methodology changes, and upstream source disruptions. • Build and maintain a library of quality checks tailored to the unique requirements of AI-powered customer experiences. • Ensure the agent consistently surfaces reliable, accurate, and internally consistent information across all supported use cases.

• Define and own the product roadmap for core areas of the Energy Utility Platform — market access, flexibility marketing, procurement, and the optimization layer that connects devices to markets — with a focus on delivery and measurable outcomes • Hands-on in execution: writing specifications, running discovery sprints, prioritizing backlogs, and releasing engineering — this is not a strategy-only role • Shape the energy products of the future: direct marketing, expanded flexibility participation, and new forms of market access for customers, while addressing the regulatory and infrastructure challenges that make this possible • Work closely with Energy Operations (domain experts, regulatory contexts) and engineering to ensure product decisions are grounded in market reality • Navigate complex regulatory environments (German energy market, MaKo, grid tariff structures, billing) and translate them into actionable product requirements • Balance product thinking with the discipline to solve difficult infrastructure problems — you need both • Report to the Director, Product Heartbeat AI and contribute to portfolio strategy decisions

• Own the end-to-end product vision, strategy, and multi-year roadmap for aspects of our Supplier Network, with a strong emphasis on AI-forward capabilities such as intelligent buyer-supplier matching, predictive risk and fraud detection, generative AI for onboarding and insights, autonomous workflows, and adaptive trust/identity verification. • Define and scale two-sided growth loops that increase buyer demand, supplier participation, transaction velocity, and network effects while maintaining marketplace integrity and buyer trust. • Lead product strategy for supplier business, including subscriptions, premium visibility, marketplace access, sourcing events, APIs, and new AI-powered premium services. • Partner deeply with Engineering, AI/ML, Design, Data Science, Sales, Marketing, and Customer Success to deliver high-impact features from concept to launch and iteration. • Drive product-led growth (PLG) motions tailored to enterprise procurement workflows, balancing speed with long-term platform health and second-order network effects. • Engage directly with customers and prospects to validate needs, gather insights, and shape differentiating solutions in supplier profiles, risk, trust, and identity management. • Define north-star metrics and success frameworks focused on network liquidity, activation rates, monetization, retention, and AI-driven business outcomes. • Monitor emerging trends in AI, two-sided marketplaces, trust/identity providers, and spend management to keep Coupa at the forefront of innovation.