AI Operations Manager

📋 Description

• • Own the end-to-end delivery of high-stakes AI data projects for Fortune-500 and hyper-growth enterprise clients, translating complex business objectives into precise annotation strategies that power the next generation of LLMs, computer-vision models, and GenAI products.
• • Architect and maintain detailed project plans that map every task, dependency, resource, and risk from kickoff to final hand-off; continuously recalibrate scope, timelines, and budgets as client needs evolve while protecting SuperAnnotate’s margin and reputation.
• • Serve as the single point of accountability for clients and internal stakeholders, running weekly steering committees, daily stand-ups, and ad-hoc deep-dives to surface blockers early, celebrate wins, and keep all parties aligned on KPIs such as throughput, quality, and cost per labeled record.
• • Recruit, vet, onboard, and coach globally distributed annotation teams (in-house, freelance, and vendor partners), writing role-specific training curricula, creating gold-standard examples, and instituting performance dashboards that drive 95 %+ accuracy and on-time delivery.
• • Translate technical requirements into clear instructions for annotators—leveraging Python scripts, SQL queries, and SuperAnnotate’s SDK to automate repetitive tasks, validate edge cases, and surface data anomalies before they reach the client.
• • Design and enforce rigorous quality-assurance workflows: define sampling rates, build consensus rules, run inter-annotator agreement tests, and present root-cause analyses that turn quality insights into process improvements and product feedback for our engineering teams.
• • Monitor real-time project health through custom Looker dashboards; proactively flag scope creep, resource bottlenecks, or quality drift, and negotiate change orders or timeline extensions with clients backed by data-driven impact assessments.
• • Champion a culture of continuous improvement by documenting playbooks, contributing to internal tooling roadmaps, and leading post-mortems that distill lessons learned into scalable templates used across the entire Customer Success organization.
• • Collaborate cross-functionally with Sales, Solutions Engineering, Product, and R&D to pilot new annotation types (e.g., RLHF for LLMs, 3-D cuboids, multimodal fusion), ensuring each experiment is production-ready and aligned with SuperAnnotate’s strategic vision.
• • Represent SuperAnnotate at industry conferences, webinars, and client QBRs, showcasing case studies that highlight how your operational excellence accelerates AI innovation and delivers measurable ROI.