Legal Engineer

Job description

Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work. Grounded in a singular system of truth, Filevine brings together data, documents, workflows, and teams into one unified platform—where modern legal work happens with clarity and consistency. Powered by **LOIS**, the Legal Operating Intelligence System, Filevine connects context across every matter to transform legal operations from reactive to proactive. LOIS reads, understands, and reasons across your data to surface insight, automate complexity, and give professionals the clarity and confidence to see more, know more, and do more. Fueled by a team of exceptional collaborators and innovators, Filevine’s rapid growth has earned AI awards and recognition from Deloitte and Inc. as one of the most innovative and fastest-growing technology companies in the country. Our AI and Machine Learning teams build systems that **help legal professionals reason over case data**, **understand documents**, **generate work products**, retrieve **grounded answers**, and automate **high-value legal workflows**. This work requires strong technical execution, but also deep legal judgment. We need people who can help define what high-quality legal AI output looks like and ensure our systems work in the context of real legal practice. We’re looking for a **Legal Engineer** to work closely with our Machine Learning Engineers, Product, Software Engineering, and Data Annotation teams. This role sits at the **intersection** of **legal practice**, **AI product development**, **data quality**, and **model evaluation**. It is not a traditional legal counsel role; we want someone who can translate legal workflows into **clear product** and **ML requirements**, evaluate **model behavior**, identify **legal edge cases**, and help build AI systems that legal professionals can trust. ### Key responsibilities - Work closely with ML engineers, data scientists, product managers, and engineering teams to improve AI capabilities across Filevine’s legal workflows - Translate legal tasks, documents, workflows, and user expectations into clear requirements for AI systems, prompts, retrieval pipelines, evaluations, and product behavior - Define what “good” looks like for legal AI outputs, including accuracy, completeness, grounding, citations, tone, usability, and appropriate handling of uncertainty - Review and evaluate model outputs across use cases such as case summarization, document analysis, deposition workflows, demand generation, medical chronology, intake, task automation, and matter-level Q&A - Create and maintain evaluation rubrics, golden answers, annotation guidelines, failure-mode taxonomies, and workflow-specific quality standards - Partner with data annotation teams to design review workflows, calibrate reviewers, resolve ambiguity, and improve the legal relevance and consistency of labeled data - Identify legal and workflow-specific edge cases, hallucination patterns, citation failures, missing context, and product behaviors that could reduce user trust - Provide structured feedback to ML and Product teams on model performance, product gaps, data quality issues, workflow friction, and opportunities for improvement - Help refine prompts, retrieval strategies, agent workflows, and human-in-the-loop review patterns for legal use cases ### Who are we looking for - Strong communication and writing skills in English - JD or equivalent legal training, with practical experience in a law firm, legal department, government legal office, or legal operations environment - Strong understanding of legal workflows, legal documents, matter management, and how attorneys, paralegals, and legal staff work in practice - Ability to evaluate legal content carefully, identify missing context or inaccuracies, and explain why an AI output is or is not useful to a legal professional - Strong interest in AI, machine learning, legal technology, document intelligence, and workflow automation - Experience with AI tools, prompt engineering, evaluation workflows, document review, knowledge systems, or data annotation processes is a plus - Ability to create clear rubrics, examples, test cases, review guidelines, and structured feedback for technical and non-technical audiences - Comfort working closely with engineers, ML teams, product managers, designers, and data annotation partners in a fast-moving product development environment - Experience in litigation, personal injury, insurance defense, immigration, mass torts, corporate legal, or other high-volume legal workflows is a plus - Ability to meet periodically in our office, as we value in-person collaboration