PW

Member of Technical Staff, Front-end

Parallel Web Systems
Posted onFeb 17, 2026
LocationSan Francisco, California, United States | Palo Alto, California, United States (On-site)
Employment typeFull-time

At Parallel Web Systems, we are bringing a new web to life: it’s built with, by, and for AIs. Our work spans innovations across crawling, indexing, ranking, retrieval, and reasoning systems. Our first product is a set of APIs for AIs to do more with web data.

We are a fully in-person team based in both San Francisco and Palo Alto, CA. Our organization is flat; our team is small and talent dense.

We want to talk to you if you are someone who can bring us closer to living our aspirational values:

  1. Own customer impact -It’s on us to ensure real-world outcomes for our customers.

  2. Obsess over craft -Perfect every detail because quality compounds.

  3. Accelerate change -Ship fast, adapt faster, and move frontier ideas into production.

  4. Create win-wins -Creatively turn trade-offs into upside.

  5. Make high-conviction bets -Try and fail. But succeed an unfair amount.

Job: You will design, build, and refine the product experience that serves as the best showcase of what our powerful APIs are capable of. You will build the developer API playground that developers love to use. You will ensure our front-end is fast, reliable, and delightful to use, while maintaining a codebase that’s scalable and easy to evolve.

You: Are an expert at modern front-end frameworks, maintainable UI architecture, and building UIs that feel fast and snappy. You care about your work feeling seamless and intuitive to users, and about building interfaces that have the highest level of polish.

Our founder is Parag Agrawal. Previously, he was the CEO and CTO at Twitter. Our investors include First Round Capital, Index Ventures, Khosla Ventures, and many others.

Parallel Web Systems

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Parallel Web Systems builds web search and research APIs purpose-built for AI agents, providing production-grade infrastructure that outperforms humans and leading AI models on complex research benchmarks.

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