Revenue Operations Lead - AI Business
ProlificNew York$120k – $150kPosted 23 February 2026
Job Description
Revenue Operations Lead – AI Business (
US East Coast)
Prolific
Prolific is building the world’s most trusted human feedback infrastructure for AI, research, and insight. We work with frontier AI labs, enterprise AI teams, and leading academic institutions to deliver high-quality, ethical, and scalable human data.
As our AI business scales rapidly, we’re investing in strong, disciplined
Revenue Operations to support increasingly complex sales motions, managed services delivery, and long-term customer value.
The Role
We’re looking for a Revenue Operations Lead to scale Prolific’s AI revenue engine across Sales, Customer Success, and Services. This role is explicitly RevOps-focused: systems, data, forecasting, process, and performance, not end-to-end marketing ops ownership.
You’ll act as the operational backbone for our AI commercial organization, partnering most closely with Sales leaders, Account Executives, Customer Success, and BI, while working in tight collaboration with Marketing Ops and Research RevOps leads.
You will support our growing Sales and CS presence across New York and San Francisco, with strong overlap with GTM leadership and exec stakeholders.
Your mandate is to i ncrease revenue efficiency and i mprove forecasting accuracy and confidence while e nsuring high-quality, timely reporting and performance visibility
This role sits at the heart of Prolific’s AI commercial engine. As we scale enterprise and frontier AI customers, revenue complexity increases and RevOps becomes a strategic accelerator.
You’ll help ensure we can scale fast, predictably, and intelligently, with sales teams focused on closing, CS focused on value, and leadership confident in the numbers.
If you thrive in ambiguity, care deeply about revenue mechanics, are a strong collaborator, and want to shape how an AI infrastructure company scales commercially, we would love to hear from you.
What you'll be doing
Revenue systems infrastructure
Own and continuously optimize Prolific’s revenue systems, with HubSpot at the core.
Ensure clean, scalable workflows across sales, renewals, expansions, and services delivery.
Partner with Marketing Ops, RevOps for Research, BI and Support Ops on system boundaries, integrations, and data contracts (not duplicate ownership).
Identify gaps, document requirements, and lead implementation of scalable RevOps solutions.
Revenue data, analytics forecasting
Build and maintain revenue reporting and dashboards across pipeline, bookings, delivery, retention, and expansion.
Own forecasting rigor for the AI business: deal hygiene, stage definitions, pipeline reporting, confidence modelling, and variance analysis.
Partner closely with BI to improve data models, definitions, and executive-level reporting for MBRs and other forums.
Improve data quality and visibility across long, multi-stakeholder AI deal cycles.
Sales Customer Sucess Process Design
Design, document, and optimize end-to-end revenue processes (opportunity - contract - delivery - renewal/expansion).
Identify bottlenecks across Sales, CS, and Managed Services and drive pragmatic fixes.
Ensure operational readiness for complex deal structures, pricing models, and delivery commitments.
Sales partnership commercial enablement
Act as a trusted operational partner to Sales and CS leadership.
Support territory design, capacity planning, quota modelling / monitoring and pipeline health.
Enable new AI products, packaging, and commercial models from a revenue mechanics perspective (not marketing execution).
Support sales teams with insight, tooling, and clarity, not overhead.
Execution operating rhythm
Balance proactive, high-impact RevOps initiatives with responsive support for Sales and CS teams.
Establish clear operating cadences, documentation, and performance reviews and MBRs for the BU and Sales Leadership.
Support change management as Prolific evolves its AI offerings and revenue mix.
Essential skills and experience:
Prov ... (truncated, view full listing at source)
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