Discovery Technical Operations Specialist

Posted 27 Days Ago
Be an Early Applicant
2 Locations
In-Office
170K-220K Annually
Senior level
Artificial Intelligence • Natural Language Processing • Generative AI
The Role
Build and operate enterprise discovery across the full EDRM lifecycle, including legal holds, preservation, collection, processing, review, and production. Manage discovery technology, vendors, active litigation matters, and information governance programs. Partner with Legal, Security, IT, Engineering, and outside counsel to govern data sources, improve retention and disposition workflows, integrate AI and automation, develop internal tools, and report on discovery operations and risk.
Summary Generated by Built In
About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role

Anthropic's legal team operates at the frontier of some of the most consequential legal and regulatory questions of our time — from landmark copyright matters to first-of-their-kind AI regulatory frameworks emerging across dozens of jurisdictions simultaneously. As we scale, the volume and complexity of our discovery and information governance obligations are growing rapidly.

We are looking for a Discovery Technical Operations Specialist to join our Litigation and Regulatory team and help build out Anthropic's discovery operations from the ground up, support active matters, and help drive information governance maturation. This is a unique opportunity to be a part of a critical function at one of the most closely watched companies in the world. You will work hand-in-hand with our discovery leads, litigation and regulatory counsel, outside counsel, discovery vendors, and cross-functional partners such as Security and IT to manage retention, preservation, collection, and production of electronically stored information (ESI) across active matters. Beyond matter-level support and programmatic development of discovery systems and processes, you will also help execute the development of Anthropic's broader information governance program, including data classification standards and defensible disposal practices that keep pace with a rapidly scaling AI company's evolving data landscape.

The right person for this role will be equal parts technical operator and operational project manager.

Key responsibilities
  • Build and operate discovery operations across the full EDRM lifecycle (preservation, collection, processing, hosting, review, and production including for novel and AI-specific data types)

  • Support the operational design and execution of the legal hold program including custodian identification workflows, hold issuance and tracking, periodic re-notification, custodian acknowledgments, and defensible release

  • Support and improve the discovery technology stack including RelativityOne, in-place preservation and collection tooling across Slack, Google Workspace, and internal systems, and supporting analytics and review platforms including configuration, access controls, templates, and reusable workspaces

  • Partner with discovery team, in-house counsel, outside counsel, vendors, and internal technical teams; coordinate matter execution, status, and escalations

  • Partner with Security, IT, and product engineering to support Anthropic's data landscape, instrument new data sources for hold and collection, and ensure each ESI source has a governed retention, hold, and disposition path

  • Improve and support the operational layer of Anthropic's information governance program: retention schedule execution, classification rollout, defensible disposition workflows, and data-inventory maintenance in close partnership with the Discovery Lead and information governance stakeholders

  • Integrate AI and automation into the EDRM lifecycle: generative-AI-assisted review, advanced analytics, custom Relativity applications, and agentic workflow automation for intake, hold tracking, status reporting, and internal documentation

  • Support active litigation, government investigations, and regulatory inquiries as the operational counterpart on the matter team coordinating workstreams, managing vendor execution, and surfacing operational risk and cost trade-offs to counsel

  • Design and build internal tools to streamline and manage critical discovery workflows (legal holds, preservation, collection, ECA, and production), and develop dashboards that report on data management trends and cross-matter discovery status

Minimum qualifications
  • Hands-on discovery experience across the full EDRM lifecycle, with demonstrated ownership of operations on complex matters in an in-house legal department, government agency, law firm, or vendor

  • A track record of supporting complex discovery operations functions 

  • Working knowledge of major discovery platforms (Anthropic uses RelativityOne), including administration, search and analytics, AI/TAR workflows, custom application development, and AI workflows

  • Strong understanding of the Federal Rules on discovery and evidence, ESI preservation obligations, and proportionality, with the operational fluency to translate those obligations into workflows

  • Experience operating discovery across modern enterprise data sources Slack, Google Workspace, mobile, and engineering systems and an understanding of how to bring novel data sources under preservation and collection

  • Strong project management instincts and a track record of running multiple concurrent matters and programs under tight deadlines, with composure and precision

  • Demonstrated ability to communicate technical discovery and operational concepts clearly to attorneys, executives, engineers, and non-technical stakeholders

Preferred qualifications
  • 6+ years of hands-on discovery experience across the full EDRM lifecycle

  • Experience standing up discovery operations at a young and/or fast-scaling company, particularly in the context of new kinds of ESI

  • Experience embedding with engineering or product teams to define discovery and information governance requirements, prioritize roadmap, and ship hold-capable and collection-capable features into core enterprise tools

  • Hands-on integration of generative AI and agentic workflows (e.g., Claude, Claude Code, or similar) into operational discovery work project tracking, status reporting, internal documentation, custom tooling, and script maintenance

  • Technical fluency working with engineering teams and modern infrastructure APIs, cloud (AWS, GCP), data pipelines, and version control and comfort writing, reading, or maintaining small scripts where useful

  • Experience operating information governance programs at scale including retention scheduling, data classification, defensible disposition, and data mapping across heterogeneous enterprise data sources

  • Experience with applying AI and automation to discovery operations, including generative AI for review, agentic automation, and operational tooling for hold tracking, reporting, and documentation

  • A collaborative, hands-on orientation, with integrity and genuine curiosity about building operational programs in a fast-moving environment


The annual compensation range for this role is listed below. 

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:
$170,000—$220,000 USD
Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Skills Required

  • Hands-on discovery experience across the full EDRM lifecycle, including ownership of complex matter operations
  • Experience supporting complex discovery operations functions
  • Working knowledge of major discovery platforms, including administration, search and analytics, AI/TAR workflows, custom application development, and AI workflows
  • Strong understanding of Federal Rules on discovery and evidence, ESI preservation obligations, and proportionality
  • Experience operating discovery across Slack, Google Workspace, mobile, engineering systems, and other modern enterprise data sources
  • Strong project management skills and ability to manage multiple concurrent matters and programs under tight deadlines
  • Ability to communicate technical discovery and operational concepts to attorneys, executives, engineers, and non-technical stakeholders
  • Bachelor's degree or equivalent combination of education, training, and experience
  • At least 6 years of hands-on discovery experience across the full EDRM lifecycle
  • Experience establishing discovery operations at a young or rapidly scaling company
  • Experience partnering with engineering or product teams to define discovery and information governance requirements and ship hold-capable or collection-capable features
  • Experience integrating generative AI and agentic workflows into discovery operations and tooling
  • Technical fluency with infrastructure APIs, AWS, GCP, data pipelines, version control, and small scripts
  • Experience operating information governance programs involving retention schedules, data classification, defensible disposition, and data mapping
  • Experience applying AI and automation to discovery operations, including AI-assisted review, agentic automation, and operational tooling

Anthropic Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anthropic and has not been reviewed or approved by Anthropic.

  • Equity Value & Accessibility — Equity stakes are considered exceptionally lucrative due to significant valuation growth and access to secondary liquidity opportunities. Equity is positioned as a major driver of total compensation and potential wealth creation.
  • Healthcare Strength — Comprehensive medical, dental, and vision coverage for employees and dependents is complemented by fertility support and mental-health resources. This breadth indicates strong foundational healthcare coverage.
  • Parental & Family Support — Twenty-two weeks of paid parental leave and additional caregiver or medical leave accommodations reflect robust support for families. These policies prioritize caregiving needs within the benefits package.

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The Company
HQ: San Francisco, California
2,500 Employees

What We Do

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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