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Software Engineer — Agentic Search Systems

$80–$150/task

Remote

Role overview

We're looking for engineers who have shipped production search systems (especially agentic ones now that we're in the era of LLMs and agents) and are thinking hard about the requirements and optimizations of those systems.

You've probably:

- Owned relevance or retrieval on a system real users depended on

- Decided how to quantify impact and improvements with these systems.

- Built out systems related to agentic search.

- Scaled data infrastructure to power modern search systems.

This is a 25-minute conversational interview. No coding, no take-home. We want to hear how you actually think about search quality, evaluation, and the tradeoffs you've made in real systems. Bring war stories — the messier and more specific, the better.

If your interview stands out, we'll follow up with a paid 30-minute live conversation with our team — $200 for your time, paid on completion of the call.

If that sounds like you, apply and complete the interview. We review every submission.

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Future of work · September 2026

How big is the remote / hybrid opportunity?

Remote work is already huge — but the bigger story may be the hundreds of millions of jobs that could still move beyond geography.

Global remote and hybrid work opportunity infographic

Remote work already connects millions of people with companies they would never have been able to work for a decade ago. But compared with the size of the global labour market, it may still be early.

The interesting number is not only how many people work remotely today — it is how many roles could plausibly become remote or hybrid next.

The chart above starts with roughly 3.3 billion people employed worldwide. Around 300 million jobs are already remote or hybrid, while an additional pool of roughly 250 million roles could potentially move in that direction as technology, workflows and company culture continue to change.

Skills are becoming more portable

This matters because more work can increasingly be matched to expertise rather than location. AI training and evaluation are a good example: companies need lawyers, engineers, designers, editors, researchers, finance professionals and many other specialists to help improve AI systems.

For workers, that creates access to projects outside their local market. For companies, it expands the talent pool from one city or country to the world.

Explore remote opportunities →