Issaquah, Washington, United States
The next decade of enterprise software belongs to the products that operate themselves. I have spent the last 13 years at ServiceNow building toward that future, and the 12 years before it at Microsoft learning how to engineer for scale that does not forgive shortcuts. Across both, the throughline is the same: I build the infrastructure that lets enterprise platforms become autonomous, observable, and trustworthy at the size where one bad alert costs millions and one good prediction saves a quarter. What I am known for is taking operational chaos and turning it into measurable customer outcomes. MTTR down 70%. Alert noise reduced by 80%. Outage prediction accuracy lifted to 70%. A central control plane orchestrating millions of automated workflows across 45+ data centers at 99.99% availability. A telemetry product that went from idea to $100M+ in organic revenue inside 12 months, scaling from zero to 60+ across product and engineering while serving 1,800+ enterprise customers. My conviction on AI is simple and a little contrarian. AI is not a sidecar feature you bolt onto a mature product. It is the substrate. Every product I own at ServiceNow is being rebuilt so that AI is the native fabric, agentic orchestration handles root cause and remediation, and the human stays on the loop rather than inside it. The customers winning right now are the ones running self-service platforms. The customers losing are the ones still running ticketed services dressed up in modern UI. The technical depth is real. I built predictive analytics platform that powers anomaly detection, event correlation, and alert enrichment. I reframed observability across the company onto OpenTelemetry standards as a decentralized self-service platform unified by a single API. I designed the data lake that now informs roadmap and revenue decisions across multiple product lines. I serve as the go-to executive on the highest-severity customer outages, because preserving trust during the worst moments is where renewals are actually earned. What I am looking for next is a VP or Head of Product role where observability, AIOps, autonomous operations, or enterprise cloud infrastructure is core to the business, and where the leadership team is ready to commit to AI-native product strategy rather than AI-flavored marketing. I am open to companies between Series C and post-IPO, ideally with a hard technical problem and a customer base that punishes hand-waving. If that is the shape of what you are building, I would welcome the conversation. Reach out: [email protected] or 425.922.7517.
Lead product management for observability, monitoring, big data infrastructure, and the AI-native central control plane orchestrating millions of workflows across 45+ data centers at 99.99% availability. Direct 14+ product managers and a data science team, partnering with CTO, SVP, and VP leadership on multi-year vision and autonomous operations strategy. Established the observability and AIOps vision and delivered a MaaS architecture standardizing telemetry across 10+ product lines. Built the ServiceNow data lake powering usage analytics and roadmap decisions. Drove AI-native strategy as fabric rather than sidecar, and shipped the agentic orchestration roadmap moving the platform toward autonomous operations with human-on-the-loop oversight. Reframed observability as a decentralized self-service platform on OpenTelemetry standards: data collection, ingestion, alerting, bring-your-own-ML, automated workflows, NLP-driven troubleshooting, and agentic root-cause remediation unified through a single API across 45+ data centers, while addressing governance, compliance, and sovereignty requirements without business disruption. Generated $100M+ in organic revenue within 12 months on a customer-facing telemetry product, scaling team and footprint from zero to 60+ across 1,800+ enterprise customers. Cut MTTR 70% and alert noise 80%. Increased outage prediction accuracy to 70%. Recognized with two ServiceNow Technology Awards for Innovation.
Thirteen-year arc through Microsoft engineering and program management organizations, advancing from Development Lead to Senior Technical Program Manager on Windows Intune, the cloud-based device management service for enterprise endpoints. Owned scale, capacity, and reliability for infrastructure supporting millions of devices under firm performance and uptime expectations. Architected the zero-downtime service upgrade capability for Windows Intune, enabling seamless version upgrades for enterprise customers across the device management platform without disrupting in-flight workloads. Improved Intune service performance by 25% and cut performance testing cycle time by 70% by building an automated performance measurement framework that drove targeted fixes across feature teams. Led end-to-end delivery of mission-critical enterprise applications, managing combined in-house and offshore engineering teams, and consistently delivered programs valued up to $4M on time against firm release deadlines.
Software engineering roles building early enterprise and e-commerce platforms, establishing the development principles, systems integration discipline, and customer-driven engineering instincts that continue to inform current product strategy.