Anthropic

Staff Software Engineer, Product

Anthropic
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8 days ago
Seattle, WA, USA +2 moreStaff+
H1B Sponsor

Base Salary

$320k - $405k/yr

Responsibilities

  • Set technical direction for the Claude product and its features.
  • Build and ship user-facing features for Claude’s web and desktop experiences.
  • Own the product quality bar, including visual quality, latency, responsiveness, and reliability.
  • Collaborate with product managers and designers to understand user needs, scope features, and make tradeoffs.
  • Iterate on the product using user feedback and internal testing.

Requirements

  • At least 5 years of experience building consumer-facing web products with a strong focus on UI quality and user experience.
  • Proficiency in React, Next.js, TypeScript, and Node.js.
  • Strong understanding of user experience, page-load performance, latency, responsiveness, reliability, and cross-device behavior.
  • Ability to collaborate closely with designers and product managers in an iterative product development process.
  • Bachelor’s degree or an equivalent combination of education, training, and/or experience in a relevant field or demonstrated through relevant coursework, training, or professional experience.
  • Formal certifications or education credentials beyond the stated equivalent combination are not required.

Benefits

  • Hybrid work with staff expected to be in an Anthropic office at least 25% of the time, with some roles requiring more office time.
  • Visa sponsorship may be available, supported by an immigration lawyer.
  • Competitive benefits including generous vacation and parental leave, flexible working hours, and office collaboration space.
  • Optional equity donation matching.
  • Anthropic is a public benefit corporation focused on building reliable, interpretable, and steerable AI systems.

Tech Stack

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Anthropic

About Anthropic

501-1,000 employees

We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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