Jobs at Harvey

Own research and implementation of post-training methods for legal language models, including supervised fine-tuning, reinforcement learning, reward design, verifiers, preference modeling, evaluations, and distributed training. Lead experiments from research direction through production deployment, while debugging training instability, reward hacking, and divergence. Build rigorous evaluation systems and production-quality Python code for long-horizon legal reasoning and agentic workflows.

Build and scale infrastructure for post-training open-weight language models, including distributed training, reinforcement learning rollouts, agent environments, evaluation systems, experiment tracking, and model serving. Own performance, reliability, GPU utilization, checkpointing, failure recovery, observability, and production integration. Partner closely with researchers to turn experimental workflows into dependable systems and accelerate development of legal AI capabilities.

Build synthetic data pipelines, evaluation systems, benchmarks, verifiers, rubrics, and quality metrics for legal AI models and agentic workflows. Partner with researchers, legal experts, and customers to investigate model failures, validate metrics, maintain data quality and provenance, and convert expert feedback and product usage into training signals and improved evaluations.

Own Harvey’s shared cloud-first IT infrastructure, infrastructure-as-code frameworks, automation, provisioning, monitoring, backups, resilience, certificates, DNS, and office technology standards. Build CI pipelines and configuration management for platforms such as Okta, Jamf, Intune, and Google Workspace. Improve change control, documentation, alerting, recovery runbooks, and identity lifecycle workflows while partnering with Security, Networking, and platform owners.

Own and scale Harvey’s people systems, primarily Workday HCM, Benefits platforms, and Ashby. Configure workflows, security, approvals, integrations, and lifecycle processes; translate business needs into scalable solutions; lead testing, troubleshooting, release management, audits, and data governance. Partner with People Operations, Benefits, Recruiting, Payroll, Finance, Legal, and IT on enhancements and process improvements while documenting standards and advising senior stakeholders.

Own and consolidate the customer support knowledge base for human specialists and an AI Support agent. Audit, migrate, structure, and maintain articles, troubleshooting guides, and product documentation. Keep content current with weekly product releases, use ticket and search data to identify gaps, and build AI-assisted workflows for content creation and maintenance. Partner with Product, Engineering, AI Support, and Enablement SMEs to validate and improve knowledge quality, accuracy, and adoption.

Own and optimize Harvey’s Zendesk platform and broader Customer Experience systems stack, including Planhat and Sierra. Configure workflows, automations, integrations, reporting, and AI features; manage platform governance, testing, deployment, documentation, and troubleshooting. Lead enhancement projects, prioritize requests, maintain operational SLAs, support user acceptance testing, and partner with CX Operations, Support, Customer Success, Data, Integrations, and Security teams.

Own Harvey’s finance applications portfolio, including NetSuite, procurement, spend, billing, and revenue systems. Lead discovery, process design, architecture, roadmap prioritization, configuration, integrations, automation, testing, and deployment across global finance processes. Partner with Accounting, FP&A, Revenue Operations, Procurement, Tax, Security, and Business Technology to solve complex multi-entity, multi-currency, billing, and revenue recognition challenges. Mentor peers and establish application quality, governance, and change-management practices.

Own complex global People Operations programs from planning through go-live and handoff, including geographic expansion, entity formation, M&A integrations, EOR and vendor transitions, and payroll migrations. Build program plans, coordinate cross-functional stakeholders, manage risks and decisions, lead executive and employee communications, and create repeatable playbooks and operating processes. The role requires hands-on execution, strong judgment, stakeholder management, executive communication, and effective use of AI.

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.