Senior Project Manager - Generative AI Data Operations

AI data program delivery

Take responsibility for a portfolio of small and medium projects or a large program with several workstreams. The scope covers generative AI data operations, including collection, labeling and evaluation, with delivery plans that coordinate priorities, milestones and handovers across time zones.

You will define the approach independently and involve leaders when a situation falls outside standard practice. Planning and accountability for quality and client outcomes are shared with the senior quality analyst and relevant operational leads.

Portfolio responsibilities

• Establish regular status, risk and executive reporting, agreeing scope and budgets with account and operations leadership.
• Forecast annotator and evaluator capacity, securing the necessary mix of shifts, throughput and skills across internal teams and suppliers.
• Align acceptance standards, audits, guidance and corrective actions with the senior quality analyst so that project quality stays consistent.
• Work with operations technology colleagues to identify manual effort and trial templates, scripts, robotic process automation or API based workflows, expanding successful approaches.
• Set supplier expectations, service levels and working procedures, then review performance and arrange improvements or changes where needed.
• Track budgets, spending and margins, using change orders to protect financial outcomes.
• Investigate root causes of problems, prepare corrective plans and escalate major risks with clear alternatives and consequences.
• Lead client planning and periodic business reviews, explaining results, risks and proposed next steps.
• Keep privacy, data handling and access requirements in place throughout the portfolio.

Team coordination

Coach P1 project managers and C2 to C3 coordinators in planning, quality assurance and tools, supporting their onboarding and development. Coaching does not require formal line management, while the wider scope also includes collecting feedback, training, performance reviews and support for staffing and retention.

Coordinate onboarding, departures and employee needs with people support, finance and recruiting colleagues. Maintain clear communication and current operating procedures, and support team cohesion.

Work with recruiters on language requirements, upcoming assignments and candidate status. Review proposed candidates and determine whether assessments, interviews or client presentations are appropriate.

Background and skills

A bachelor’s degree or equivalent experience in business, operations, data, engineering or a related area is expected. You need 2 to 3 years leading portfolios or substantial programs in AI data, content review, annotation or a similar field.

Capacity planning, supplier coordination and quality systems experience are central; experience testing or expanding automation is helpful. Strong spreadsheet, project board and basic business intelligence skills are expected, with SQL or ETL familiarity an advantage.

You should communicate clearly with senior clients, negotiate and escalate effectively, and judge tradeoffs among scope, time, cost and quality. Distributed global work requires intermediate to advanced English and a coaching approach.

Additional qualifications include near native English writing and editing, practical generative AI experience, quality testing or rubric development, and awareness of AI safety or ethics. Familiarity with annotation and model evaluation tools, conceptual understanding of code and data workflows, multilingual ability and independent remote workflow management are also relevant; coding is not required.