Security Risk Analyst, Risk Engineering en Anthropic

Híbrido - San Francisco, CA, United States

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The Security Risk Analyst in Anthropic's Risk Engineering team leads the identification, prioritization, and treatment of the company’s most critical security risks. Working closely with Security Engineering, the analyst builds quantitative FAIR-based risk models, develops reusable risk assessment methods, and communicates findings to leadership. The role requires strong quantitative skills, experience with FAIR, Python/R/spreadsheets, and deep understanding of security risk management in AI systems.

Salary

USD 270,000 - 345,000

Requirements

Skills

  • Owned security or technology risk analysis end to end, qualitative and quantitative
  • Hands‑on FAIR-style quantification experience, including scenario decomposition, calibrated estimation, and Monte Carlo simulation in Python, R, or spreadsheet tooling
  • Ability to thrive in ambiguity and frame questions into analyzable problems
  • Defensible severity and likelihood assessment with honest uncertainty statements
  • Technical security depth to decompose an attack path with security engineers
  • Capacity to compress complex risk positions into concise executive summaries
  • Experience using Claude or other LLMs as daily working tools and reviewing model output critically
  • Low ego, collaborative mindset and commitment to AI safety
  • Applied FAIR‑CAM or other structured approach to control effectiveness and attack path modeling (strong candidate)
  • Built or operated a cyber risk quantification program or turned quantitative analysis into tooling, templates, or training (strong candidate)
  • Helped define risk appetite or tolerance thresholds used for decision making (strong candidate)
  • Background in security engineering, detection, threat intelligence, actuarial science, or decision science (strong candidate)
  • Familiarity with AI‑specific security risks such as goal or intent modification (strong candidate)

Responsibilities

  • Enable leadership and partner teams to make risk‑informed decisions by driving ambiguous risk questions to documented decisions and communicating trade‑offs
  • Lead quantitative analysis of top security risk scenarios using FAIR, calibrated estimation, and simulation, working with engineers and presenting actionable results
  • Partner with Security Engineering to assess threat scenarios and control effectiveness, aligning investment with actual risk and sequencing remediation
  • Frame escalations and risk treatment decisions with clear recommendations, honesty about uncertainty, and re‑evaluation triggers, and pressure‑test those decisions with risk owners
  • Shape the analysis and narrative behind leadership risk reviews, and help define risk appetite and metrics the organization should measure
  • Use AI and automation to scale risk analysis, owning calibration and quality review to maintain trustworthy outputs
  • Turn one‑off analyses into reusable methods, templates, and training, increasing self‑service risk analysis and raising the analytical quality of the risk register

Technologies

FAIRPythonRSpreadsheetsAI and automationClaude LLM

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