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HumanSignal

Senior Frontend Engineer

9.0/10

HumanSignal

$115,000 – $195,500 USD
Remote
senior
about 4 hours ago
aidevtechPythonDjangoJavaScriptTypeScriptReactOpenAI APISparkBigQueryKafka

AI Summary

The vacancy is well-structured with clear expectations and compensation, though company details could be improved.

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Description

What you'll do

  • •Build and maintain frontend components and views for labeling, review, and evaluation workflows with performance, accessibility, and scalability in mind.
  • •Own outcomes, not tasks: refine scope, suggest trade-offs, propose simpler approaches, and land increments that deliver value fast.
  • •Partner with Product & Design from discovery to delivery: clarify user jobs, write lightweight RFCs/PRDs, and shape scope and milestones.
  • •Prototype to de-risk UX; use flags/gradual rollouts; gather feedback from users/support and iterate after releases.
  • •Raise the bar on FE standards: state management, testing, error boundaries, a11y, i18n, and developer ergonomics.
  • •Partner with Support to investigate production issues, reduce UX papercuts, and turn learnings into fixes.
  • •Engage with our open-source community (issues, discussions) to understand real-world needs and improve developer experience.
  • •Participate in architecture discussions and code reviews; mentor teammates and improve patterns across the codebase.

Requirements

  • •Senior-level experience shipping production React/TypeScript apps (HTML/CSS mastery; ES6+; a11y).
  • •Strong product sense: you’ve made scope/trade-off decisions and iterated based on real-world usage and feedback.
  • •Fluency with modern FE tooling (e.g., Vite/Webpack, Jest/Cypress) and state-management patterns.
  • •Comfort collaborating with APIs and occasionally touching backend code (Django/REST familiarity is a plus).
  • •Excellent communication at a Senior IC level —you write clear RFCs/PRDs, give actionable reviews, and present trade-offs well.
  • •Nice to have: Experience with data/ML tools, OSS, design systems, or performance profiling.
  • •Familiarity with feature flags/gradual rollouts and qualitative feedback loops (support forums, user sessions).
  • •Prior work on complex, data-heavy UIs (review tools, multi-step workflows, or IDE-like apps).
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