Working within a shared, organization-wide framework for triage, prioritization, delivery to Engineering, and feedback updates, you will lead a cross-functional virtual team that brings product management discipline and deep support expertise to in-market feedback, covering both incident and non-incident items. Run the post-launch feedback process: Lead a cross-functional virtual team that applies a shared, organization-wide framework for triaging, delivering, and closing the loop on in-market customer feedback, including incident and non-incident items. Help evolve the framework with partner teams across the organization. Build insights dashboards and accelerate decisions: Define the data model, metrics, and insights dashboards that give Product, Engineering, field, and support leaders a clear view of status, decisions, and impact. Use telemetry, analytics, and AI to combine feedback signals, identify patterns, remove duplicates, and assess impact and urgency. Use automation to route feedback, maintain traceability, and shorten the time from intake to decision. Drive adoption across the team: Coach peer product managers and partner teams to use the process consistently. Measure adoption and quality, and improve the system based on results and feedback. Build a clear and technically credible customer voice: Bring together post-launch signals from support, field, customers, partners, product usage, and research. Engage customers when it sharpens a decision: Work primarily through internal teams and available evidence, and meet directly with enterprise customers, security operations teams, or identity practitioners when firsthand context is needed to clarify architectures, workflows, integrations, technical blockers, or expected product behavior. Validate and diagnose product signals: Work with field, support, Product, Engineering, and subject matter experts to assess reproducibility, severity, scale, telemetry, workarounds, and possible root causes, separating product gaps from configuration or operational issues. Influence product direction: Turn complex customer scenarios into clear problem statements, requirements, and tradeoffs that Product and Engineering leaders can use when making decisions about quality, supportability, architecture, adoption, and investment. Balance customer impact with technical feasibility, dependencies, and capacity. Drive decisions and closure: Deliver qualified feedback to the right Product Engineering owners, make sure each item receives a clear decision, rationale, timing, and accountable follow-through, and keep field and support teams updated on outcomes. Partner with clear roles: Work with support, field, and subject matter expert teams across the organization, with each team contributing expertise in its area. Bring product management and support expertise without duplicating their roles. Provide technical thought leadership: Serve as a trusted advisor on security operations, threat protection, identity, and post-launch product health. Explain complex technical issues clearly to practitioner and executive audiences. Bachelor's Degree AND 8+ years experience in product/service/program management or software development Bachelor's Degree AND 12+ years experience in product/service/program management or software development OR equivalent experience. 4+ years experience taking a product, feature, or experience to market (e.g., design, addressing product market fit, and launch, internal tool/framework). 6+ years experience improving product metrics for a product, feature, or experience in a market (e.g., growing customer base, expanding customer usage, avoiding customer churn). 6+ years experience disrupting a market for a product, feature, or experience (e.g., competitive disruption, taking the place of an established competing product). Experience turning post-launch signals from customers, support, product data, research, or product usage into prioritized product requirements or recommendations for Engineering. Experience analyzing technical evidence such as telemetry, logs, support patterns, reproducibility, severity, workarounds, or root-cause hypotheses to guide product decisions. Experience working with data protection, information governance, compliance, device and endpoint management, or identity technologies in enterprise deployments, including discussing technical tradeoffs with customers and engineers. Experience influencing senior Product and Engineering stakeholders across organizations without direct authority. Experience with post-launch product health, customer escalation patterns, supportability, adoption, or customer experience programs. Experience building feedback systems, insights dashboards, regular review processes, or ways to communicate priorities and decisions across large organizations. Experience using AI-assisted analysis, analytics, product data, and automation to summarize and categorize feedback, identify patterns, Experience turning signals from customers, field teams, support, telemetry, research, or product usage into clear, evidence-based requirements or recommendations for Engineering. Experience leading cross-team or virtual-team initiatives to design and implement processes, systems, or operating rhythms adopted by multiple teams. Experience defining metrics and building or directing insights dashboards used to drive prioritization or business decisions. Experience analyzing technical evidence such as telemetry, logs, support patterns, reproducibility, severity, workarounds, or root-cause hypotheses to guide product decisions. Experience applying AI to synthesize feedback, detect patterns and duplicates, recommend priorities, automate routing, and reduce the time from intake to decision.