Lead Technical Analyst, Workspace Ai, Trust and Safety

Google Google · Big Tech · Seattle, WA +1

Lead Technical Analyst for Workspace AI Trust and Safety, defining strategy and technical roadmap for AI safety, prompt injection evaluations, and misuse prevention. Designs and implements scalable anti-abuse detection and action systems, including AI agent frameworks. Investigates novel GenAI failure modes and establishes benchmarking/evaluation protocols. Advises stakeholders and mentors analysts.

What you'd actually do

  1. Define the technical roadmap and long-term strategy for AI safety, prompt injection evaluations, and misuse prevention across Workspace AI Products.
  2. Lead the design and implementation of scalable anti-abuse detection and action systems, including the "AI agent" frameworks used to automate enforcement.
  3. Lead the investigation of novel and failure modes for GenAI products (e.g., sociotechnical harms, adversarial misuse) and establish benchmarking and evaluation protocols.
  4. Act as a trusted advisor to executive stakeholders in Engineering and Product, translating safety and security risks into actionable business insights and influencing product design to prioritize safety.
  5. Mentor analysts, review technical work, and elevate the team’s capabilities in data extraction, statistical analysis, and machine learning.

Skills

Required

  • data analysis
  • security threat detection
  • abuse investigation
  • Python
  • SQL
  • Machine Learning
  • Anomaly Detection
  • AI models

Nice to have

  • building and deploying anti-abuse systems at the scale of Google Cloud or Workspace
  • exploratory data analysis
  • statistical analysis
  • identifying non-obvious patterns in datasets
  • navigating ambiguity
  • solving problems in the AI safety domain
  • critical thinking
  • written and verbal communication
  • articulating technical safety concerns to executive leadership

What the JD emphasized

  • AI safety
  • prompt injection evaluations
  • misuse prevention
  • anti-abuse detection
  • AI agent frameworks
  • novel and failure modes for GenAI products
  • benchmarking and evaluation protocols
  • safety and security risks
  • AI Principles

Other signals

  • AI safety
  • anti-abuse detection
  • evaluation protocols
  • AI Principles