• Translate the VP’s strategy into a sequenced backlog of problems, user stories, and acceptance criteria that the Engineering team can deliver continuously. • Keep work “thin-sliced” so the team can ship frequently, learn quickly, and reduce risk through iteration. • Maintain a disciplined cadence of backlog refinement, sprint readiness, and scope negotiation to keep delivery predictable without slowing innovation. • Leverage your hands-on DevOps experience and expertise in the real-world workflows of the professionals you’re building for - especially cloud operators and practitioners. • Use firsthand domain knowledge and ongoing customer conversations to identify friction, gaps, and opportunities for differentiation. • Prioritize enhancements that materially improve outcomes: speed, reliability, clarity, safety, governance, cost impact, or operational simplicity. • Often speak with customers (aiming for 3-5 calls a week) and cross-functional DoiT stakeholders regularly to test ideas, validate assumptions, and pressure-test tradeoffs. • Communicate clearly and confidently: share concepts early, take feedback openly, synthesize input into decisions, and explain “why” in a way that builds trust. • Rely on your hands-on, DevOps experience to go deep with stakeholders (internal/external) into the technical details of the problem, our solution, and the contexts and environments in which both of these exist. • Support beta/design-partner motions where appropriate by shaping hypotheses, success criteria, and rollout plans. • Operate as a core member of the component’s Engineering team - present in daily collaboration, crisp in decision-making, and pragmatic about constraints. • Partner with Engineering leads on sequencing, technical tradeoffs, and delivery planning - ensuring product intent survives implementation realities. • Ensure the component is cohesive across UX, APIs, data, and operational behavior - and that it meets a high bar for reliability and customer trust. • Define what “success” means for the component with clear metrics (adoption, activation, workflow completion, time-to-value, retention, reliability signals, customer-reported impact). • Instrument learning: make sure releases are measurable and that insights reliably flow back into prioritization. • Own release readiness for your component: documentation, enablement inputs, and clear communication of what’s new and why it matters. • Ensure product requirements account for real-world cloud environments: IAM boundaries, auditability, guardrails, and safe defaults. • Partner with security, support, and customer teams to anticipate edge cases and ensure the component earns trust over time.