Job Description

About the team

This role is part of the Regional Partner Success team, to support driving quality improvements, leveraging key data inputs from Quality Data Measurement. This role will be a key conduit between the TnQ TikTok team and our partner teams and will be expected to drive performance metrics with our moderation teams across our Partner footprint.

Responsibilities

1. Vendor Operations Management

- Own end-to-end operational delivery of Live Content Moderation across assigned vendor partners, ensuring SLA compliance for response time, accuracy, and throughput

- Design and implement vendor operating cadences including partner huddles, weekly business reviews, and monthly strategic planning sessions

- Monitor real-time moderation queues and escalation pathways; proactively identify and resolve operational bottlenecks, capacity gaps, and quality drift

- Coordinate queue go-live activities with stakeholders ensuring vendors are capacity-ready, trained, and reporting is configured prior to launch

- Develop and maintain vendor playbook documentation covering operational procedures, escalation protocols, and crisis response workflows

2. Quality Assurance & Data-Driven Performance

- Own and maintain quality dashboards and performance scorecards across all partner sites; ensure data integrity and reduce discrepancies in reporting

- Drive RCA (Root Cause Analysis) deep dives on underperformance with vendor QA leads; surface feedback and propose actionable solutions to improve metrics

- Leverage Quality data to identify accuracy gaps and drive continuous improvement initiatives

- Publish consolidated performance reports spanning markets, covering KPIs; present insights and recommendations to stakeholders

- Identify trends and anomalies through data analysis; propose proactive interventions before issues escalate

3. Policy Rollout & Compliance

- Project-manage the end-to-end rollout of policy changes, upskilling programs, case alignments, and new processes across vendor partners in coordination with POMs

- Provide operational support for major policy launches (e.g., large-scale policy framework updates), including test execution, documentation QA, and readiness verification

- Where markets span multiple regions, serve as the cross-region/cross-partner liaison — aligning on quality standards, policy interpretation, and ecosystem changes

- Ensure vendor QA teams maintain a high bar of policy knowledge; conduct regular policy calibration sessions and alignment checks

- Oversee and communicate any misalignments from quality measurement processes to prevent impact on BPO accuracy and reporting

4. Stakeholder Management & Partnership

- Build and maintain strong relationships with internal stakeholders including Inhouse T&S, Global Training, Quality, Policy Enforcement, Product teams and other XFNs

- Create a strong partnership cadence with vendor leadership to enable joint action planning and metric ownership on quality-related matters

- Advocate for vendor moderation teams internally — surface their challenges, feedback, and operational constraints to drive systemic improvements

- Conduct triage during critical events, risk escalations, and major incidents at LOB and market level; coordinate cross-functional response efforts

- Attend internal calibration and alignment sessions; provide necessary clarifications to partners based on community guidelines

5. Gen AI Integration & AI-Augmented Moderation

- Champion the adoption and optimization of Gen AI tools within vendor operations, including AI-assisted triage, auto-labeling, and intelligent queue routing

- Collaborate with T&S product and engineering teams to pilot and scale AI-powered moderation features across vendor sites; manage UAT, feedback loops, and iteration cycles

- Evaluate vendor readiness for AI-augmented workflows; design upskilling programs to build AI literacy and prompt-engineering capabilities within vendor QA and moderation teams

- Monitor AI model performance metrics (precision, recall, false positive/negative rates) in partnership with ML teams; ensure AI outputs align with policy intent and cultural nuance

- Drive operational playbooks for human-in-the-loop (HITL) workflows, ensuring moderators effectively validate, override, and provide feedback on AI-generated decisions

- Stay current on emerging Gen AI applications in Trust & Safety (e.g., multimodal content analysis, adversarial robustness testing, red-teaming) and advocate for their operational integration