Our client, a leading Tech company are going through a period of growth to keep up with customer demand.

We are looking for a high-impact engineer focused on the building and maintenance of massive-scale distributed platforms. You won't just build features; you will solve the challenges of rendering complex data for millions of concurrent users. This role prioritizes engineering excellence, from deep-dive performance profiling to the adoption of cutting-edge build-time optimizations.


Responsibilities

• Performance Engineering: Lead initiatives to analyse and optimize frontend rendering and core application health by identifying and resolving complex bottlenecks.
• Feature Architecture: Design , implement and maintain complex, highly interactive features using TypeScript, React, and Electron.
• Platform Scalability: Optimize data communication and backend architecture to ensure system responsiveness and efficiency across distributed cloud environments.
• Operational Excellence: Improve team velocity by setting frontend engineering standards and integrating sophisticated unit and E2E testing into CI/CD pipelines.
• Quality Assurance: Drive the stability of the platform by investigating regressions and implementing systemic improvements to ensure high-quality, reliable releases.

Requirements

• Education: Bachelor’s degree (or higher) in Computer Science or a related technical discipline.
• Experience: 5+ years of professional experience, with a proven track record of significantly improving frontend performance and load metrics for global, high-traffic applications.
• Deep React Expertise: Advanced experience with React Compiler rollouts, hydration optimizations, and managing rendering efficiency across massive component libraries.
• Systems Architecture: Proven ability to design designing and developing high-quality software services and high-concurrency backends (Node.js/Go) that maintain sub-second latency for large-scale request volumes.
• Testing & Stability: Advanced proficiency in Playwright, Cypress, and Jest, specifically in the context of visual regression and identifying critical bug patterns in automated pipelines.
• Data-Driven: Experience building event-tracking analytics pipelines to enable data-informed A/B testing of UI/UX changes.