Why this grade This listing scored 58/100, which is a C. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 15 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 15 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Role specificity 3 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
This listing does not state a salary
$125k – $188k
That is the middle half of what comparable roles paid on this board over the last 90 days — 59 listings that did publish a figure, median $160k. It is not this employer's offer, and we have no idea what they pay. It is only what the rest of the market advertised.
hn-hiring
We build high-throughput crawling and structured data extraction infra designed for AI agents and LLM pipelines.
If you’ve built scrapers recently, you already know the state of the market:
- Traditional proxy providers (Bright Data, Oxylabs, Smartproxy, Proxybase) give you raw IPs or massive unparsed HTML blobs, leaving you to deal with DOM bloat, token waste, and brittle parsing pipelines.
- Modern tools like Firecrawl or Jina made clean Markdown extraction easy for hobby setups, but they often struggle when you throw heavy SPAs, high-concurrency jobs, or hardened anti-bot walls (Cloudflare Under-Attack / Turnstile, Kasada, DataDome) at them.
- Rolling your own Playwright / Puppeteer cluster works until target sites deploy new JA4/TLS fingerprints, and your data team ends up spending 30% of their sprints fixing broken crawlers instead of shipping product.
We're tackling this by combining a low-latency Rust fast-fetch engine (JA4/TLS and HTTP/2 frame emulation) with an isolated stealth browser fleet, zero-code schema validation (JSON Schema/Pydantic), and native Model Context Protocol (MCP) support.
Trade-offs / where we fit: If you just need to curl a few static Wikipedia pages, a 10-line Python script is better and cheaper. But if you need reliable, structured data out of bot-defended sites without babying headless browsers, that's what we do.
We're looking for:
1. Rust Systems Engineer: High-concurrency network I/O, Axum/Tokio, TLS/BoringSSL fingerprinting, proxy routing matrices, and low-latency data pipelines.
2. Browser Security Engineer: Deep familiarity with browser internals (Firefox/Chromium source), canvas/WebGL/audio fingerprint evasion, CDP/WebDriver stealth, and familarity with anti-bot defenses.
Our stack: Rust, Next.js 16/React 19, TypeScript, hardened Firefox/dwx_crawler, Linux/Xvfb, SQLite WAL/Postgres.
If interested, shoot an email to [email protected] (or [email protected]) with your GitHub, a project you built or broke, and what you find interesting in this space. No formal cover letter needed.
Apply for this role Opens datamint.xyz — the employer's own page, as linked by the source that listed this role
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Where this listing came from
- 02 Oct 2026 Hacker News first sighting
Seen on 1 board over 7 days.