Content Risk Analyst, Asci

Amazon Amazon · Big Tech · IN, KA, Bengaluru · Operations, IT, & Support Engineering

This role focuses on improving AI models for Alexa experiences by performing data annotation, quality auditing, red teaming, customer feedback triage, and incident monitoring. The analyst acts as a human-in-the-loop, using AI tools to support their work and ensure quality and safety standards are met. The primary output is curated data and validated model behavior, with a secondary involvement in agentic systems through human oversight.

What you'd actually do

  1. Perform multi-domain data annotation and golden dataset curation for AI model improvement, following established SOPs and quality benchmarks
  2. Execute adversarial testing across multiple Alexa experiences (Alexa+, Ring, Automotive, Kids), using AI to generate diverse attack vectors and edge cases
  3. Classify and triage daily customer feedback records per SOPs, using AI to pre-sort and surface emerging patterns
  4. Monitor for policy violations and emerging issues per established protocols, using AI to track incident patterns across workstreams
  5. Identify and propose process improvements to enhance operational efficiency, using AI to prototype automation and workflow optimizations

Skills

Required

  • Experience in Artificial Intelligence/Machine Learning (AI/ML) Standards Law
  • 1+ years of experience in content moderation, data annotation, AI/ML operations, or compliance operations
  • Ability to follow SOPs and apply judgment in a fast-changing environment

Nice to have

  • Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
  • Experience with AI annotation tools, LLM outputs, or model evaluation frameworks
  • Familiarity with red teaming, content safety, or responsible AI operations
  • Exposure to incident management or escalation handling workflows

What the JD emphasized

  • AI model improvement
  • red teaming
  • customer feedback triage
  • incident monitoring
  • AI annotation tools
  • LLM outputs
  • model evaluation frameworks

Other signals

  • AI model improvement
  • human-in-the-loop
  • red teaming
  • customer feedback triage
  • incident monitoring