Anthropic

Software Engineer, Safeguards

Anthropic
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12 months ago
San Francisco, CA, USASenior / Staff+
H1B sponsor

Base Salary

$320k - $425k/yr

Responsibilities

  • Develop monitoring systems to detect unwanted behaviors from API partners and potentially take automated enforcement actions.
  • Surface detected behaviors in internal dashboards for analyst review.
  • Build abuse detection mechanisms and infrastructure.
  • Surface abuse patterns to research teams to support model hardening during training.
  • Build robust, reliable, multi-layered defenses for real-time improvement of safety mechanisms at scale.
  • Analyze user reports of inappropriate content or accounts.

Requirements

  • Bachelor’s degree in Computer Science, Software Engineering, or a comparable field, or equivalent experience.
  • 5–10+ years of experience in a software engineering position, preferably focused on integrity, spam, fraud, or abuse detection and mitigation.
  • Proficiency in Python and TypeScript.
  • Ability to work across the stack.
  • Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.

Benefits

  • Full-time employees receive equity, benefits, and may receive incentive compensation.
  • Optional equity donation matching is available.
  • Generous vacation and parental leave are offered.
  • Flexible working hours are available.
  • The role follows a location-based hybrid policy requiring staff to be in an office at least 25% of the time, with some roles requiring more.
  • Visa sponsorship may be available, supported by an immigration lawyer.
  • The company provides office space for collaboration.

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Anthropic

About Anthropic

5,001-10,000 employees

Anthropic builds large language models and the Claude AI assistant for developers and enterprises, offered via API access and enterprise plans. Founded in 2021 and headquartered in San Francisco, it distributes Claude through its own platform and via partners such as Amazon Bedrock and Google Cloud’s Vertex AI. Its work emphasizes model reliability, interpretability, and practical tooling for tasks like coding assistance, analysis, and customer support automation.

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