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Head of Legal Operations

Job Overview

Location

San Francisco

Job Type

Full-time

Category

Software Engineering

Date Posted

June 4, 2026

Full Job Description

đź“‹ Description

  • • Own and build the legal operations engine for a high-growth AI company, scaling legal function efficiency without linear headcount growth through automation, playbooks, and AI-assisted workflows
  • • Lead end-to-end contract lifecycle management (CLM), including intake, routing, template governance, repository organization, and reporting, in close alignment with RevOps and Sales Ops
  • • Serve as the legal lead on Order Form, CPQ, and contract-management system decisions, driving cross-functional workstreams on behalf of the Chief Legal Officer
  • • Design, operate, and continuously improve the Slack-based legal intake and triage pipeline, ensuring requests are classified, drafted, reviewed, and closed with speed and accuracy
  • • Lead legal technology and AI strategy with a bias toward building over buying — design and implement agentic AI workflows (e.g., Claude Cowork) before evaluating off-the-shelf tools
  • • Build and maintain the legal data and reporting layer, including cycle times, deal volume, risk snapshots, and program health metrics that inform leadership decision-making
  • • Own knowledge management: curate, version, and maintain up-to-date playbooks, legal briefs, and templates as the single source of truth for the legal team and broader organization
  • • Manage outside counsel operations, including panel selection, engagement terms, spend tracking, and matter management, with a focus on cost control and scope alignment
  • • Establish and enforce operational cadences such as intake SLAs, approval gates, and cross-functional handoffs with Sales, Finance, and Security to ensure accountability and speed
  • • Partner with the Chief Legal Officer to design the legal team’s operating model as the company scales toward IPO, and own program management of all legal initiatives from conception to execution
  • • Assist on M&A and strategic transactions as needed, including due diligence support, data room management, and integration operations
  • • Drive adoption of legal tooling and workflows across Legal, RevOps, Sales Ops, Finance, Security, and IT, translating complex operational design into clear, usable processes
  • • Become a thought leader in AI-native legal operations, helping define the future of modern legal function infrastructure in high-velocity tech environments

🎯 Requirements

  • • 7+ years in legal operations at a high-growth technology company, including ownership of a legal-ops program (not just supporting one)
  • • Deep hands-on experience with CLM systems and legal tooling — selection, implementation, and day-to-day operation
  • • Fluency with data and reporting — ability to build dashboards and metrics that leadership actively uses
  • • Fluency — or a clear path to fluency — in building and managing agentic AI workflows (e.g., Claude Cowork), with a bias toward building over buying
  • • Strong cross-functional operator who can drive adoption across Legal, RevOps, Sales Ops, Finance, Security, and IT
  • • Clear, direct communicator who can translate operational design into usable workflows for non-legal teams

🏖️ Benefits

  • • Competitive compensation, including meaningful equity
  • • 100% coverage of medical, dental, and vision insurance for employee and dependents
  • • Flexible PTO policy including company-wide Winter Break (offices closed from Christmas Eve to New Year's Day)
  • • Paid parental leave
  • • Fertility and family-building stipend through Carrot
  • • Company-facilitated 401(k)
  • • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities

Skills & Technologies

Apache Spark
Onsite
Degree Required

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BaseTen Inc.
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About BaseTen Inc.

BaseTen provides a serverless, GPU-accelerated platform that lets machine-learning teams deploy, scale and monitor custom models behind autoscaling inference endpoints. The service abstracts infrastructure management, supports PyTorch, TensorFlow and Hugging Face artifacts, and offers built-in observability, A/B testing and fine-tuning. Customers integrate via REST or GraphQL APIs and pay only for compute used. Founded in 2019 and headquartered in San Francisco, BaseTen targets data scientists and product teams seeking production-grade ML serving without Kubernetes complexity.

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