We are looking for a high-ownership Operations Manager to lead and scale multilingual AI data annotation projects. The candidate should have strong experience in managing large-scale data/annotation operations, workforce management, client communications (including US/foreign clients), and end-to-end delivery with strong quality controls. Key ResponsibilitiesProject & Operations ManagementTake ownership of end-to-end operations for large-scale data annotation/labeling projects across languages.Run pilots successfully and transition them into scaled delivery models.Handle day-to-day operations: execution, driving daily volumes, tracking progress, flagging risks, and daily client/internal reporting.Set clear goals, targets, KPIs and KRAs for the team and ensure consistent achievement.Work closely with the product/tech team to improve workflows, tools, and productivity.Proven ability to drive tightly controlled operational metrics with SLA adherence.Strong process orientation and business acumen.Quality & TrainingBuild and manage QA processes (Dedicated QA teams / distributed QA model).Analyse training needs and conduct training sessions for teams on tools, guidelines & quality expectations.Ensure feedback loops are set and corrective actions are implemented promptly.Continuously optimize quality, productivity and process efficiency.People & Stakeholder ManagementManage and mentor a young team of editors, annotators, reviewers and leads (50300+ workforce scale).Demonstrate strong people engagement, motivation and team-building skills.Liaise with foreign clients (primarily US) professionally for updates, alignment and escalations.Vendor management for external language support (foreign languages + regional languages).Process Excellence & ImprovementSuggest improvements at every level of operationspeople, tools, SOPs, QC, training and delivery framework.High sense of ownership with a strong bias for action and ability to work in dynamic & unstructured environments. Technical Skills RequiredAdvanced Excel & Google Sheets expertise including formulas, dashboards, pivot tables, reports, data modeling.Experience using scripts/macros/automations for process efficiency (Google Scripts, Basic Python, or Excel VBA advantage).Strong analytical skills & comfort with data-driven decision making.Familiarity with annotation tools, workforce management systems, QC systems (added advantage).Bonus: Experience in AI/ML data ops, content moderation, transcription, or linguistic projects. Eligibility & Preferred Background47 years in Operations Management, Project Management or Data/Annotation Ops.Ability to work across cross-functional teams including Product, QA, HR, and Clients.Strong communication skills impeccable English (spoken + written). Hindi preferred.Bachelors or Masters degree from a reputable institution.