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As a Senior Full Stack Software Engineer, you will embed with enterprise customers to implement AI systems, design workflows, and operationalize software solutions, enhancing efficiency and driving measurable outcomes.

As an Enterprise Customer Success Manager, you'll integrate AI in legal workflows, guide customers, build relationships, ensure value realization, and work with sales teams for expansions and renewals.

The Staff Software Engineer will design and build AI platform systems, focusing on context management and model integration, driving infrastructure quality for legal applications.

The Staff Software Engineer, Backend Platform at Harvey will develop and maintain backend frameworks, create and improve APIs, introduce modern architecture patterns, and enhance reliability and observability in the platform to boost engineering productivity.

Lead adoption and value realization of Harvey's AI platform for mid-market legal and in-house teams. Manage 40+ accounts, implement integrations, deliver training, design scalable playbooks and self-help materials, track success metrics, drive renewals and expansions, and relay customer feedback to product teams.

Drive enterprise sales of Harvey's AI platform to law firms and professional services. Manage full sales cycle for named accounts, exceed revenue targets, deliver demos, build long-term relationships, collaborate with product and engineering, and develop scalable sales playbooks.

Owner of Support Operations analytics: build and maintain dashboards and recurring reports, track cSAT/TTR/QA/escalations, instrument Zendesk, connect support to product/customer data, design feedback loops, measure AI-driven support impact, quantify cost of bugs/features, and support ad-hoc analysis for leadership.

Lead implementation and adoption of Harvey's AI/LLM platform for 40+ mid-market clients. Provide training, drive engagement and advocacy, monitor health and success metrics, create scalable playbooks and documentation, surface customer feedback to product teams, and ensure renewal and expansion readiness.

Own support analytics for User Operations: build recurring reports and self-serve dashboards, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support data to product/customer sources, quantify operational cost of bugs, measure AI-driven support impact, and deliver ad hoc analyses to inform Product, Engineering, and leadership.

Own support analytics for User Operations: build dashboards and recurring reports, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support to product/customer data, quantify operational costs of bugs, and measure AI-driven support performance.