Manager of Legal Engineering

Legal work is becoming agentic, and the firms that win will be the ones whose AI actually understands the substance of their matters. NetDocuments sits on the context layer of the legal industry — the documents, matters, and relationships that constitute the working memory of a law firm. Our products increasingly turn that position into structured, permission-aware legal intelligence: maps of matters, semantic layers, and agentic capabilities that let AI start work already understanding what a matter is about, rather than re-reading five thousand documents to figure it out.

NetDocuments is seeking a Manager of Legal Engineering to own the substantive legal quality of that intelligence — and to build the discipline of legal engineering inside our R&D organization.

This is not a sales engineering or customer-facing solutions role. This is a build role at the center of R&D. You will be the lawyer in the room when we decide what an agent needs to know about a litigation matter versus an M&A deal versus a regulatory investigation — and you will encode that judgment into schemas, skills, and evaluation harnesses that ship in production. A pure technologist would model a matter one way; you know that a litigation matter lives and dies on its claims, parties, key events, and procedural posture, and you can express that knowledge in a form an agent can use.

You'll operate as a player-coach: a senior individual contributor who also builds and leads a small, special-forces team of legal engineers, working across every product team in R&D.

You will:

• →Own how NetDocuments structures legal knowledge. Define what must be captured, structured, and surfaced for different matter types and practice areas across products like our Legal Context Graph, improving substantive outcomes for legal professionals, efficiency, and comprehensiveness across the full breadth of legal work.
• →Build the evaluation discipline for legal AI at NetDocuments. Design and run evaluation harnesses that define what "good" looks like for legal work product, briefs, analyses, extractions, and agent outputs, and prove with rigor that each iteration of our products is better than the last.
• →Develop our legal skill strategy. Author, test, and validate the skills (structured, executable domain knowledge) that let agents perform substantive legal tasks correctly, and build the testing scaffolding that validates they actually matter.
• →Define legal taxonomy and structure. Bring frameworks like practice-area ontologies, document typologies, and matter lifecycles into a coherent semantic layer that agents and products can rely on.
• →Hire and lead a small team of legal engineers while remaining deeply hands-on yourself.
• →Work across all of R&D. Partner with Product, Engineering, and Design teams across our AI, user experience, and platform groups, serving as the substantive legal authority for agentic product decisions.
• →Anticipate the questions a legal professional would ask of a matter, a document set, or an agent's output, and ensure our products can answer them.

• →The People!
• →90% healthcare premiums company covered
• →HSA company contribution
• →401K match at 4% with immediate vesting
• →Flexible PTO (typically 3 to 4 weeks a year)
• →10 paid holidays
• →Monthly contributions for life activities & wellness
• →Access to LinkedIn Learning with monthly dedicated time to explore

• A law degree and real practice experience, including a minimum of 1–3 years as a practicing attorney (firm or corporate legal department), followed by a career that has stayed close to the legal industry through legal technology, knowledge management, innovation leadership, legal data, or similar disciplines.
• Genuine fluency with modern AI development. You build with tools like Claude Code or Codex, are comfortable in a repository, and may be an active GitHub contributor. You don't need to be a production engineer, but your team should ideally be fluent in building, starting with you.
• A careful, methodical, rigorous mind. This role is about provability: structured thinking, careful taxonomy, and disciplined testing, not vibes.
• Deep understanding of how legal work actually happens, what a litigation matter requires versus a transaction, how lawyers reason about documents, and what substantive quality means in legal work product.
• Comfort operating as a super-IC leader in a high-autonomy environment. You receive context and strategic direction, then determine the execution approach independently.
• Energy and conviction about where this is going. You see the agentic future of legal work clearly and want to build it, not study it.

• Experience building or evaluating legal AI products at a legal technology company, law firm, or corporate legal department.
• Familiarity with legal taxonomies and standards such as FOLIO.
• Published work, open-source contributions, or community involvement within the legal engineering, legal innovation, or legal AI ecosystem.
• Experience designing evaluation frameworks, benchmark datasets, or quality measurement systems for domain-specific AI applications.
• Experience hiring and leading small, high-leverage technical, legal, or hybrid teams.