Role Purpose

Appen's GenAI Project Delivery team sits at the intersection of AI development and real-world data quality, executing the annotation, evaluation, and data collection work that shapes how frontier models perform. The purpose of this role is to drive end-to-end delivery excellence across GenAI projects by ensuring task configuration, contributor performance, and data quality outcomes stay tightly aligned to client expectations. This is a hands-on, cross-functional role with influence over delivery standards, client outcomes, and the continuous improvement of how Appen executes at scale.

Your Impact

Coordinate assigned project workstreams - covering productivity, qualification, training, crowd communications, and QA - to ensure on-time delivery against execution standards

Deliver high-quality annotation and QA during POC and pilot phases to establish quality benchmarks and de-risk new client relationships from day one

Partner with Client Partners and Pilot Teams to validate quote assumptions, including time-per-task and quality requirements, before finalization

Analyze datasets to surface patterns, insights, and optimization opportunities that inform automation strategy and drive thought leadership content for customers

Support Project Managers and Client Partners as the AI expert point of contact across client meetings, workshops, QBRs, and status updates

Maintain version control and change communication protocols to ensure contributors are informed of guideline updates prior to launch and throughout production

Translate QA findings into targeted improvements to supporting materials, reducing recurring annotation errors and improving overall data quality

Provide data-backed findings and consultancy insight to strengthen Appen's advisory value during critical early project phases and ongoing client relationships

What You Bring

Proven experience coordinating or delivering data annotation, content evaluation, or AI training data projects in a structured delivery environment

Strong understanding of data quality principles, QA methodologies, and annotation workflows within GenAI or adjacent AI domains

Ability to create clear, accurate contributor-facing documentation including guidelines, FAQs, and cheatsheets under tight timelines

Experience supporting pilot or POC phases, including validating operational assumptions and establishing quality benchmarks

Demonstrated ability to analyse datasets, identify patterns, and translate findings into actionable insights or process improvements

Confident communicator with experience engaging cross-functional stakeholders, including client-facing participation in meetings, workshops, or reporting cycles

Disciplined approach to version control, update management, and change communication across distributed contributor teams

Comfortable operating across multiple concurrent workstreams with a high degree of ownership and attention to delivery standards

Remote General Jobs at Appen

Remote General Jobs at Appen