Jobs at Chegg, Inc.

The Revenue Operations Manager will align Marketing, Sales, and Customer Success processes across the customer lifecycle. Responsibilities include managing HubSpot governance and handover, improving lead-to-renewal workflows, coordinating reporting and revenue processes, partnering with Finance and Decision Intelligence, documenting SOPs, training teams, and driving adoption of operational improvements and automation.

Manage enterprise SaaS customers by building relationships, driving onboarding and adoption, improving retention, renewing and expanding accounts, and translating customer needs into product solutions. The role requires French and English fluency, client data presentation, commercial focus, and experience with enterprise customers in a technology or SaaS environment. Responsibilities also include customer references, case studies, referrals, and monitoring market trends.

Lead FP&A operational activities: build and maintain financial models, own cash flow forecasting and month-end FP&A support, design FP&A data architecture, apply AI to automate workflows, deliver variance analysis and management reporting, and support ad-hoc financial analysis and business cases.

Build and own end-to-end evaluation frameworks for LLMs and multi-step AI agents, including benchmarks, automated and human-in-the-loop evaluators, golden datasets, regression suites, production monitoring, and quality dashboards. Partner with research, product, Trust & Safety, and legal teams to define rigorous metrics and translate evaluation results into training and deployment decisions. Mentor engineers and establish evaluation best practices.

Own and build Busuu’s B2B product marketing function across mid-market and enterprise segments. Define ICPs, segmentation, pricing, packaging, positioning, messaging, buyer journeys, win-loss insights, sales enablement, and launch strategy. Partner with sales, growth, marketing, product, and technology teams to establish an enterprise commercial motion and support expansion from initial mid-market deployments to larger accounts.

Design, build and deploy production-grade agentic AI systems and LLM/RAG features. Own multi-agent orchestration, prompt engineering, evaluation, and full ML lifecycle from training pipelines to online inference and monitoring. Improve ML platform and tooling (MLflow, Airflow, SageMaker, Kubernetes), collaborate cross-functionally, and lead research on advanced RAG, graph representations, and agentic evaluation.

The Facilitator will deliver academic support in Data Analytics through live sessions, tutoring, and quality assurance, while collaborating on curriculum enhancements and mentoring others.