Jobs at Prolific

Own net-new and expansion enterprise sales cycles with frontier AI labs across the West. Build relationships with AI research, product, and executive stakeholders; manage complex, multi-threaded technical sales processes; develop proposals, pilots, and success plans with cross-functional teams; forecast pipeline and communicate deal health; and relay customer feedback to product and marketing. The role requires extensive experience selling strategic B2B technology solutions, including seven- and eight-figure deals.

Leads complex AI client projects from requirements gathering through delivery, serving as the primary client contact and coordinating Sales, Operations, Product, and Engineering. Responsibilities include defining scopes and delivery plans, managing risks, quality, timelines, budgets, profitability, and KPIs, resolving execution challenges, and improving scalable processes for AI project delivery.

Partner with AI labs and enterprise teams on evaluation and human-data projects. Design methodologies, rubrics, data-collection approaches, quality frameworks, verifiers, validation systems, and reinforcement learning environments. Own projects from scoping through delivery, prototype tooling, advise customers, identify platform opportunities, collaborate with Product and Engineering, contribute to research publications, mentor colleagues, and communicate advanced AI concepts to diverse stakeholders.

Manage end-to-end operations for specialized participant pools supporting AI projects. Responsibilities include participant onboarding, verification, quality management, engagement monitoring, process optimization, project planning, documentation, and stakeholder enablement. Partner with product, technology, data, science, delivery, and customer success teams to scale manual workflows into technology-driven solutions and support high-quality human data collection for AI tasks.

Lead and grow a product marketing function for Prolific's human data platform. Own positioning, messaging, launches, packaging, and go-to-market strategy; manage three PMMs; align Product, Sales, and vertical marketing; run market and competitive research and build sales enablement.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

The Participant Recruitment Partner will identify and engage top-tier participants, manage client-specific recruitment operations, and enhance the participant pool quality through data-driven insights and collaboration.