Jobs at Clio

Owns monthly sales commission processing, audits, payouts, and sales data validation while partnering on compensation plan design, quota setting, and incentive structures. The role investigates commission inquiries, analyzes attainment and payout trends, recommends GTM improvements, and leads process, tooling, documentation, and controls enhancements. It requires strong modeling, financial acumen, stakeholder management, and experience with commission platforms, Salesforce, Excel, and Google Sheets.

Own the shared product-led growth platform supporting monetization and onboarding motions. Build account, licensing, trial, freemium, usage-cap, measurement, and PQL signal-routing infrastructure. Partner across Product, Engineering, CBS, RevOps, Sales, and Data Science to establish consistent metrics, unblock teams, and drive cross-functional adoption. Translate ambiguous priorities into a scalable platform roadmap and ship, measure, and iterate on B2B SaaS capabilities.

Serve as a legal-domain pre-sales consultant for mid-market law firms: lead discovery, deliver tailored Clio product demos and pilots, advise on safe AI adoption, convert practice needs into workflows, influence product via user insights, mentor sales and success teams, and represent Clio in legal tech thought leadership.

Design, develop, and maintain secure integrations across NetSuite, Coupa, Leapfin, and other enterprise systems. Build iPaaS workflows, custom connectors, webhook and event-driven automations, bulk synchronization processes, monitoring, error handling, and retry mechanisms. Translate finance requirements into technical specifications and data mappings, support implementation projects, document architectures, and maintain audit readiness. Apply AI-powered tooling to automate finance operations while ensuring compliance, security, and reliable handling of sensitive financial data.

Lead a team of ML engineers to design, build, and productionize LLM/GenAI and agentic systems (retrieval, tool use, orchestration). Collaborate cross-functionally with MLOps, product, and data science, review code, mentor engineers, run technical evaluations and proofs-of-concept, and ensure reliable, safe ML deployments for a large SaaS product.