Legal Operations Analyst

Ridgeline
Reno, NV; San Ramon, CA; New York, NY$110k – $140kPosted 18 April 2026

Tech Stack

Job Description

Legal Operations Analyst Are you a detail-oriented legal operations professional who enjoys turning high-volume, task-based workflows into streamlined, reliable processes? Do you get excited about using AI and modern tools to make legal work faster, smarter, and more consistent? Are you energized by supporting a busy legal team while improving systems, documentation, and day-to-day execution? If so, we invite you to be a part of our innovative team. As a Legal Operations Analyst at Ridgeline, you will play a critical role in scaling the efficiency and impact of our Legal team by owning core operational workflows and supporting contract lifecycle processes. You’ll partner closely with Legal Operations Sr. Manager and attorneys, as well as cross-functional stakeholders, to ensure requests are routed, tracked, and completed efficiently. Leveraging cutting-edge technologies and AI tools and modern CLM and workflow platforms, you’ll help automate repetitive work, improve data quality, and enhance visibility into legal operations, freeing up attorneys to focus on higher-value work. At Ridgeline, how we work matters as much as what we build. Ridgeliners act like owners, choose growth over comfort, and communicate with transparency. We assume positive intent, bias toward action, and bring solutions, not just problems. We celebrate wins, learn from setbacks, and thrive in a resilient, collaborative, high-performing culture. If this excites you, we’d love to meet you! You must be work authorized in the United States without the need for employer sponsorship. The impact you will have: Maintain and improve SOPs and checklists to standardize recurring legal processes Support end-to-end vendor contract workflows within CLM systems and prepare execution-ready documents from templates Maintain accurate contract metadata to enable reporting, searchability, and compliance tracking Operate and optimize legal technology tools including CLM, intake systems, e-signature platforms, and workflow tools Leverage AI tools to summarize contracts, draft intake notes, extract structured data, and improve documentation workflows Partner with Legal Operations Sr. Manager to identify automation opportunities and continuously improve processes Maintain and organize legal knowledge resources to enable self-service across the business Translate legal processes into clear, accessible guides for non-legal stakeholders Generate reports on legal operations metrics such as volume, cycle time, and request types Support vendor contract management and light project coordination for legal initiatives What we look for: 2–4 years of experience in legal operations, contracts, compliance, project management, or similar operational roles Hands-on experience with tools such as CLM platforms, procurement systems, e-signature tools, or workflow/ticketing systems Demonstrated use of AI tools (e.g., ChatGPT, Gemini, Glean, Copilot) to improve efficiency and workflows Strong organizational skills with the ability to manage high-volume work while maintaining attention to detail Process-oriented mindset with a natural curiosity to simplify and standardize workflows Excellent written communication skills with the ability to create clear documentation and guides Collaborative, service-oriented approach to supporting legal and business stakeholders Comfort working with data including running reports, validating information, and maintaining accuracy Willingness to learn and adopt new technologies in a fast-paced environment Bonus: Experience in a SaaS, cloud, or investment management environment Exposure to AI-assisted legal workflows such as contract review or knowledge search Familiarity with NDAs, vendor agreements, and customer contracts About Ridgeline Ridgeline is the first front-to-back system of record for investment managers. Founded by visionary entrepreneur Dave Duffield (co-founder of both PeopleSoft and Workday), the company was created to mode ... (truncated, view full listing at source)
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