About the company
We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent — but also informed.
We work with some of the most innovative teams in AI — from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world.
Responsibilities
- Design and build large-scale rendering systems for modern web applications
- Develop browser-based rendering infrastructure capable of executing complex JavaScript applications reliably
- Research how modern frontend frameworks render and deliver content
- Improve rendering quality, completeness, and performance across diverse websites
- Optimise rendering cost, latency, resource utilisation, and throughput at internet scale
- Translate rendering research into reliable production systems
Requirements
- Have 5+ years of experience as a software engineer working on production backend or infrastructure systems and are an expert in several of the following areas:
- Browser Rendering: Chromium rendering pipeline — DOM, Layout, Paint, and Compositing; JavaScript execution inside browsers and rendering lifecycle and page readiness; Headless browser execution and browser instrumentation; Chrome DevTools Protocol (CDP); Playwright, Puppeteer, Selenium, or similar frameworks
- Modern Web Applications: React, Vue, Angular, Svelte, and modern frontend architectures; Server-side rendering (SSR), client-side rendering (CSR), and streaming rendering; Single-page applications (SPA) and Progressive Web Apps (PWA); Resource loading, lazy loading, and modern JavaScript bundles
- Strong candidates may also have experience with: Building and operating high-throughput content processing pipelines at internet scale; Distributed systems design and performance optimisation; Open-source contributions or active involvement in the engineering community; Conference talks or technical publications
- We conduct coding interviews as part of the process.
Conditions
- Full ownership — small team, you own the entire infrastructure, not a slice of it
- Real scaling challenges — bursty scraping workloads, cache invalidation, multi-region, millions of daily requests
- AI-native company — your infra directly powers AI agents used by leading companies in the space.