Connecting technical work, operational risk and business outcomes.

I coordinated twelve DevOps engineers and two DBAs supporting an AWS platform handling approximately 80,000 orders per day, more than 100,000 on peak evenings and 600,000–800,000 users. I managed the backlog, priorities, blockers, adjacent-team coordination and reporting to the Head of DevOps.

I also owned PagerDuty rotations and on-call onboarding, kept root-cause actions from stalling, and ensured reliability improvements reached delivery sprints. Collaborative team outcomes included availability above 99.95%, approximately 40% lower MTTR and approximately 15% infrastructure cost savings.

As the sole Project Manager in a ten-person logistics technology team, I owned Scrum delivery across backend, frontend, systems analysis and product. The team delivered multi-stop routing, combined deliveries, dynamic order assignment and real-time balancing based on driver availability.

Operational analytics showed logistics costs reduced by up to 18% and customer wait time reduced by approximately 25%. The useful program-management lesson was to connect the engineering roadmap to observable operational measures, not only output milestones.

I do not replace technical leads or claim engineering implementations as my own. I create a delivery environment in which experts can make good decisions: explicit priorities, visible dependencies, clear ownership, timely escalation and metrics connected to business impact.

This approach has transferred across infrastructure, releases, logistics, AI delivery and service operations. The domain changes; the core work of turning ambiguity into a system teams can run remains consistent.