About Us

Legora is redefining how legal work gets done. Not built for lawyers, built with them. We work alongside the world’s best legal teams, who expect excellence, precision, and speed, and we hold ourselves to the same bar.

Our AI-native workspace lets legal professionals move faster, think more clearly, and operate with sharper precision. By analysing thousands of documents in minutes and powering end-to-end workflows, we cut through complexity, teams can focus on what matters: judgment, strategy, and outcomes.

2,100+ customers across 80+ countries trust us, including Cleary Gottlieb, Goodwin, Linklaters, White & Case, Dentons, and Barclays. We’ve scaled to $200M+ in ARR, with teams across Europe, North America and APAC, and continue to expand through acquisitions including Qura, Walter AI, Graceview, Cadastral, and Wexler.

We partner with world-class performers: including Aaron Judge and the New York Yankees, Ludvig Åberg (and his caddie), and campaigns featuring Jude Law.

Joining Legora means three things.

We lean in: ownership over titles, outcomes over intentions.

We fight for excellence: high standards, direct, ego-free feedback.

We grow together: as a team and with our customers.

Mission before ego. Everyone contributes. No one coasts.

If you’re driven by impact, pace, and raising the bar. This is the place.

The Role

We’re looking for legal professionals with strong analytical skills, technical curiosity and an interest in improving how AI supports legal work.

As a Technical Legal Engineer in the Evals function, you’ll use your legal training and practical experience to evaluate and improve Legora’s products. You’ll define what good legal work looks like, build evaluations that measure it, and help product teams understand where their systems work well and where they need to improve.

You could work across a range of legal workflows, including legal research, drafting and analysis. Depending on your focus, you may join a specific product team and develop deeper expertise in its workflows and evaluation needs.

One example is our Legal Research team, where the role combines hands-on legal evaluation with coordinating contributors who build a growing collection of research evaluations.

What You Will Be Doing

Across the Evals function, you will:

Evaluate legal outputs: Review AI-generated work for accuracy, completeness, legal reasoning and practical usability, using the judgment you would apply when reviewing legal work.

Build evaluations: Develop cases, reference answers and scoring criteria that enable consistent assessment of product quality.

Investigate failures: Identify edge cases, recurring errors and legal ambiguities, and distinguish minor issues from substantive legal risks.

Translate findings into improvements: Give product managers and engineers clear, actionable feedback and help assess whether changes improve the experience for lawyers.

Maintain evaluation quality: Keep evaluations relevant as products, models and legal requirements evolve.

If you focus on Legal Research you may also:

Own research eval coverage: Prioritise evaluations with Product and Engineering based on the roadmap, customer feedback and gaps in coverage.

Coordinate evaluation contributors: Brief and onboard drafters, allocate work, track delivery, provide feedback and coordinate expert review.

Develop complex research cases: Build cases and scoring criteria, bringing in specialist legal expertise where needed.

Test research functionality: Investigate failures, turn recurring issues into regression tests, and work with engineers to verify fixes.

Grow a reliable dataset: Help build and maintain a reviewed collection of reusable research evaluations, including contributions from students.

What You Bring

For all areas of the role, we’re looking for:

Legal training and practical experience applying legal judgment to complex work.

Strong analytical skills and the ability to explain why an output or source is useful, incomplete or incorrect.

An interest in AI products and a willingness to learn how language models and evaluations work.