• Ensure a smooth and successful product launch by supporting the execution of launch-critical features • Lead structured user engagement to inform future pi tool development, including creating interview guides and test scenarios, conducting usability walkthroughs, validating workflows, and facilitating early concept or low-fidelity testing • Collaborate with the VP of Product to capture, synthesize, and distill user feedback into actionable themes and insights • Translate agreed-upon product direction into clear user stories, functional requirements, and acceptance criteria • Partner with engineering to clarify scope, assumptions, and dependencies, ensuring alignment and timely delivery • Maintain product documentation and backlogs with a focus on launch readiness and accuracy • Establish frameworks and processes to support long-term product management execution and success as the pi platform continues to evolve and scale • Note: This role does not own product strategy, schemas, or standards; its primary focus is translating strategic direction into actionable outcomes and user-centered learning

• Partner with portfolio company leadership to define and refine product vision, strategy, and roadmaps aligned to Vista’s investment thesis and value creation plans. • Drive adoption of best-in-class product management practices across portfolio companies, with a strong emphasis on commercial outcomes (ARR growth, retention, expansion, pricing leverage). • Assess product-market fit, portfolio rationalization, platform strategy, and build/buy/partner decisions. • Translate market, customer, and competitive insights into actionable product priorities. • Establish and scale product operating models that emphasize accountability, speed, and measurable impact. • Drive consistency in product discovery, roadmap planning, delivery, and lifecycle management across portfolio companies. • Introduce and reinforce metrics-driven product management (e.g., OKRs, North Star metrics, outcome-based roadmaps). • Ensure tight integration between Product, Engineering, Sales, Marketing, and Customer Success in highly matrixed environments. • Coach, mentor, and develop CPOs, VPs of Product, and senior product leaders across the portfolio. • Leverage modern AI-powered product tools and workflows to improve product velocity and quality.

• Oversee product definition and delivery: Be directly involved in the definition, execution and timely delivery of product features, ensuring alignment with business objectives and customer expectations. • Manage product backlog: Prioritize tasks, define user stories, and work closely with the engineering team to ensure a smooth development and delivery processes. • Collaborate with cross-functional teams: Work closely with engineering, design, data, and other stakeholders to ensure a seamless product delivery from start to finish. • Optimize delivery processes: Continuously improve product workflows to enhance team efficiency, product quality, and speed to market. • Coordinate with stakeholders: Act as the main point of contact between the product team and internal stakeholders, ensuring alignment on goals, priorities, and expectations. • Build strong relationships: Foster strong, trusting relationships with both internal and external stakeholders to support seamless collaboration. • Foster collaboration: Create a transparent, communicative environment that encourages teamwork and drives collective success. • Ensure customer satisfaction: Gather feedback from stakeholders and customers, ensuring the product meets their needs and expectations, and make necessary adjustments based on their input.

• Dual Service Strategy (Inference & Training): Define the roadmap for two core service pillars: • Training Services: Orchestrating elastic, cost-optimized compute (GPU/CPU) for model training and experiment tracking. • Inference Services: Managing the deployment of models into high-availability, low-latency API endpoints. • Ease of Development & Deployment: Radicalize the user experience for ML Engineers. You will build self-service "push-button" deployment workflows that abstract away the complexity of Kubernetes and cloud networking. • Lineage & Reproducibility: Ensure every model has a clear "paper trail." You will define how we capture the lineage between data versions, training code, and production artifacts—a critical requirement for Biopharma compliance. • Observability & Governance: Build the tools to monitor model health in production. This includes infrastructure-level metrics (latency/memory) and model-level observability (drift/performance) to ensure system reliability. • Technical Stakeholder Engagement: Partner with Scientific IT and Platform Engineering to ensure our services integrate seamlessly with existing enterprise identity (IAM) and security frameworks. • Backlog & Execution: Act as the "CEO of the Service," translating complex infrastructure needs into clear, actionable epics and user stories for a high-performing engineering team.