Senior Project Manager - Generative AI Data Operations

Welo Data works with technology companies to provide datasets that are high-quality, ethically sourced, relevant, diverse, and scalable to supercharge their AI models. As a Welocalize brand, WeloData leverages over 25 years of experience in partnering with the world’s most innovative companies and brings together a curated global community of over 500,000 AI training and domain experts to offer services that span: ANNOTATION & LABELLING: Transcription, summarization, image and video classification and labeling. ENHANCING LLMs: Prompt engineering, SFT, RLHF, red teaming and adversarial model training, model output ranking. DATA COLLECTION & GENERATION: From institutional languages to remote field audio collection. RELEVANCE & INTENT: Culturally nuanced and aware, ranking, relevance, and evaluation to train models for search, ads, and LLM output. Want to join our Welo Data team? We bring practical, applied AI expertise to projects. We have both strong academic experience and a deep working knowledge of state-of-the-art AI tools, frameworks, and best practices. Help us elevate our clients' Data at Welo Data.Role Purpose:Oversees multi-project portfolios for AI training data programs. Leads delivery and scale: capacity planning, vendor management, and process automation. Ensures quality is consistent across projects, drives performance improvements, and plans work jointly with the Sr. Quality Analyst. Oversees a portfolio of programs that deliver and scale Generative AI data operations, including capacity planning, vendor management, and process automation.Key ResponsibilitiesPortfolio delivery: Plan and run a group of projects (collection, labeling, evaluation) end-to-end; set priorities, milestones, and handoffs across time zonesGovernance & reporting: Run cadence (status, risk, exec updates); align scope and budget with account and operations leadsCapacity planning: Forecast and secure rater/annotator capacity; balance shifts, throughput, and skills across vendors and internal teamsQuality consistency: Partner with the Sr. Quality Analyst on acceptance criteria, audits, and corrective actions; keep guidelines aligned across projectsProcess automation & tooling: Identify manual steps; pilot automation with Ops Tech (templates, scripts, RPA, API-driven flows); scale what worksVendor management: Set expectations, SLAs, and playbooks; review performance and drive improvements or changes as neededFinancial control: Build and track budgets, burn, and margins; manage change orders to protect financial outcomesRisk, issue & change: Lead root-cause and action plans; escalate high-impact items with options and impactClient and stakeholder management: Lead planning and QBR-style reviews; explain results, risks, and next steps in clear termsTeam enablement: Coach PMs and Coordinators on planning, QA, and tools; support onboarding and skills growth (no formal line management required)Compliance & security: Ensure data handling, privacy, and access controls are followed across all workstreamsSkillsPortfolio planning and governance across several projects at onceClear communication with senior clients and internal leaders; runs planning and QBR-style reviews. Strong use of spreadsheets, PM/task boards, and basic BI; familiarity with SQL/ETL concepts is a plus. Sound judgment on scope, time, cost, and quality trade-offs. Negotiation and escalation to resolve risks, issues, and change. Coaching mindset; guides PMs and Coordinators. Comfortable working with global, distributed teams (intermediate to advanced English)Additional QualificationsNear-native English with strong writing and editorial skillsHands-on experience with generative AI tools (text, voice, or video)Background in QA testing, rubric design, or AI safety/ethics evaluationFamiliarity with data-annotation platforms and model-evaluation toolsAbility to interpret code, datasets, and system workflows at a conceptual level (no coding required)Able to work independently and manage workflows effectively in a remote environmentMultilingual ability beyond EnglishScope and AutonomyOwns outcomes for a portfolio of small/medium projects or a large multi-workstream programWorks independently; defines delivery approach and engages leaders for non-standard itemsJoint planning and shared responsibility for quality and client outcomes with the Sr. Quality AnalystEducation RequirementsBachelor’s degree or equivalent experience in business, operations, data/engineering, or similar experience2–3 years leading multi-project portfolios or large multi-workstream programs in AI data, content review, labeling/annotation, or related fieldsBackground in capacity planning, vendor coordination, and quality systems; experience piloting or scaling process automation is a plusWe may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.