Engineer for High-Demand Online Booking Optimization

I need an experienced engineer to analyze and improve a high-demand online booking workflow so bookings can succeed reliably even under extreme traffic. I already have a working Playwright-based browser automation, but during peak demand all sessions currently land on a “high demand / unavailable” state. The goal is to improve success rate through deeper system understanding, better timing, and smarter flow control . The work involves analyzing booking flow and state transitions, understanding how availability actually appears during high demand (including delayed or staggered releases), improving timing, retries, waiting strategy, and navigation logic, eliminating race conditions and aborted navigations, and designing the automation to be long-running, reactive, and resilient while reducing dependency on opening-second spikes. Strong experience with Playwright or Puppeteer, high-traffic web systems, async control, navigation states, and event-driven logic is required, along with the ability to reason about queues, throttling behavior, and why excessive parallel sessions can reduce success. Deliverables include improved automation logic (or clear guidance with code changes), an explanation of why the new approach improves success, and logging/observability recommendations; success will be measured by meaningful improvement using only 5–6 sessions, stable behavior during peak windows, and a clear understanding of availability timing patterns. The bot or code should successfully book slots even under heavy traffic and huge amount will be given if the bot or code is working only after proof. Below i have uploaded image of how the site works if successfully enter into the page instead of high demand. Show More