AI Data Operations Lead

• Own the operational health, delivery, and outcomes for all Managed Services customers
• Lead quality programs across customers, including QA design, precision/recall analysis, accuracy tracking, and continuous improvement
• Identify root causes of quality regressions, missed SLAs, or labeling confusion — and drive fixes across tooling, training, or process
• Own escalation and risk tradeoffs when quality, safety, or customer timelines are at risk, exercising sound judgment in high-pressure situations
• Manage day-to-day relationships with BPO and data labeling partners
• Partner with vendors on staffing models, headcount planning, efficiency improvements, and performance management across time zones
• Review training materials, calibration processes, and reviewer feedback loops to ensure consistent, high-quality output at scale
• Write, test, and iterate labeling and review instructions in partnership with Product and customers
• Lead calibration processes with BPO partners to ensure consistent interpretation of guidelines and edge cases
• Work closely with Product and Engineering on AI deployments that support Managed Services customers
• Help design and refine workflows where AI augments — rather than replaces — expert human judgment
• Use operational data to inform model iteration, tooling improvements, and future product decisions
• Monitor pipeline health across human and AI-assisted workflows, identifying bottlenecks and making informed tradeoffs between quality, speed, and cost
• Act as a primary operational point of contact for Managed Services customers
• Navigate customer pressure around deadlines, errors, quality issues, and evolving requirements with calm judgment and clear communication
• Own prioritization and decision-making when information is incomplete and trade-offs are real
• Partner with GTM teams to bring Managed Services offerings to market
• Support upsells, renewals, and new customer conversations by translating operational credibility into clear value

• At least 4+ years of experience in operations roles within Trust & Safety, AI safety, content moderation, or data labeling
• Directly managed BPO or vendor-based review/labeling teams at scale
• Highly organized and comfortable owning complex, multi-threaded operational work
• Experience performing root cause analysis on operational or quality issues
• Comfortable getting into the weeds — tooling, data, training docs, edge cases — to understand what’s actually happening
• Can operate independently and take initiative in ambiguous environments
• Comfortable using data (basic data science, metrics, dashboards) to monitor performance and partner with QA or customer teams
• Excited about AI-augmented operations and believe human judgment + AI systems outperform purely manual approaches

• Experience spanning both Trust & Safety and data labeling workflows
• Experience with red-teaming or adversarial testing programs
• Background working on the customer side of BPO relationships
• Experience supporting customer-facing operations in high-stakes environments

Offers Equity