Trust & Safety Specialist III

Investigate fraud across a distributed AI workforce

In this Mexico based role, handle active trust and safety cases while supporting the wider fraud strategy program. The role involves investigations and account removals from the outset, within a detection approach that combines identity checks, behavioral signals, and account activity.

The developing trust and safety committee covers four areas: identity verification, location verification, account integrity, and detection of multiple account abuse. Your work will connect live case handling with improvements to these fraud controls.

Case responsibilities

• Triage flagged accounts, examine identity and behavior evidence, reach a decision, and process removals within policy and service deadlines.
• Review identity and location information for flagged or higher risk accounts, distinguishing genuine unusual cases from fraud.
• Prioritize manual audits by risk and the strength of available signals.
• Detect related account abuse through device and location overlap, linked accounts, and behavioral patterns.
• Form an investigative hypothesis, test it against the evidence, and record a decision that another reviewer can reproduce and audit.
• Escalate new fraud methods, incorrect flags, missed fraud, and gaps in detection rules to the fraud strategy team.
• Handle sensitive case information using GDPR aligned retention, deletion, and data handling practices.

Collaborate with research labs, Quality Strategy Architecture, and Forward Deployment Engineering when casework identifies problems with tools or processes.

Required investigation background

At least five years in trust and safety, fraud or risk investigations, or identity verification is required. Relevant environments include online marketplaces, gaming, fintech or payments, identity verification providers, and crowdsourced or gig workforce operations.

You need direct experience with signals such as device fingerprints, IP and geolocation checks, document verification, or behavioral risk scores. Experience must extend to patterns across accounts, including account farming, sharing, and linked account abuse.

Write evidence supported case notes that can stand up to an audit or appeal. You should be comfortable with ambiguous cases and substantial queues, prioritizing by risk rather than simply clearing the oldest items.

Working knowledge of GDPR or equivalent privacy obligations is required, particularly for how investigation data is handled, retained, and deleted.

Education and additional strengths

A bachelor's degree in criminology, law, criminal justice, cybersecurity, information security, data or computer science, or a related field is recommended. Equivalent practical experience is also considered.

Helpful additions include:

• CFE, CAMS, or identity verification and identity risk certifications.
• Experience with AI or machine learning annotation, RLHF, or research operations workforces.
• Familiarity with rules based fraud engines and evaluating excessive rules against useful signal quality.
• Awareness of clustering and anomaly detection approaches to fraud.
• Experience with case management, ticketing, or knowledge management tools.