Strategic Risk Analyst, Behavioral & Psychological Risk

OpenAI OpenAI · AI Frontier · San Francisco, CA · Intelligence & Investigations

This role focuses on analyzing user behavior and psychological risks in interaction with AI systems, translating these insights into risk assessments, mitigation strategies, and product guidance. It bridges clinical/behavioral expertise with intelligence analysis to identify and mitigate abuse and strategic risks, contributing to OpenAI's goal of developing AI that benefits humanity. The role involves developing behavioral risk frameworks, identifying early indicators of issues, assessing mitigation effectiveness, and contributing to incident analysis, all while working closely with various internal teams.

What you'd actually do

  1. Develop insights into how AI systems are used in complex or high-risk situations (e.g., self-harm, suicidal ideation, substance-use escalation, and threats of violence), identifying recurring patterns and emerging trends that help guide product, safety, and policy decisions.
  2. Synthesize behavioral, psychological, and intelligence signals into clear narratives about user needs, system dynamics, and potential areas of risk or vulnerability.
  3. Produce decision-ready briefs and assessments that inform product, safety, and policy decisions.
  4. Develop and refine behavioral risk frameworks, taxonomies, and indicators (e.g., severity models, escalation pathways, psychological harm categories).
  5. Identify early indicators of emerging issues and assess whether observed patterns represent meaningful safety concerns, helping prioritize and inform appropriate mitigations.

Skills

Required

  • 5+ years in forensic, clinical, trust and safety, or applied academic settings assessing risk of violence, self-harm, or addiction
  • strong mixed-methods research skills
  • familiarity with AI systems, language models, or human-AI interaction dynamics
  • translate human behavior into structured intelligence
  • connecting individual cases to system-level patterns and risks
  • comfortable working across qualitative and quantitative inputs, including casework, interaction data, research literature, and metrics
  • experience designing or using risk frameworks, taxonomies, or evaluation methods to structure ambiguity
  • communicate clearly across disciplines
  • turning complex behavioral insights into concise, actionable recommendations
  • Thrive in fast-moving, ambiguous environments
  • can prioritize effectively under uncertainty

Nice to have

  • experience working on AI safety, trust & safety, or related domains is a plus

What the JD emphasized

  • decision-ready risk assessments
  • decision-ready briefs and assessments
  • behavioral risk frameworks
  • risk assessments
  • risk