AI Engineer

Description

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 team

AI Enablement makes Legora AI-native by default. We work across three streams in parallel: building internal agents and tools, equipping teams to build their own, and owning the standards, access and guardrails that let everyone move fast safely.

We own the AI platforms and the internal products built on them. So far that includes Leya, an internal knowledge agent live in Slack that answers questions about Legora with cited sources and automates parts of our RFP and security questionnaire work. A structured, agent-readable knowledge base assembled from knowledge each domain continues to own, where agents propose changes and humans approve them. Leyf, a platform for internally built apps that lands anyone's app on shared infrastructure with guardrails scaled to how much damage it could do. And a Skills Hub, so that something one person works out becomes something the whole company can use rather than staying on their laptop.

The team is small and the mandate is large. That is the job.

What makes this hard

Legora is an AI company of around a thousand people, most already fluent and on current tools. Internal AI here is not an adoption problem. Nobody needs convincing, which means there is nowhere to hide behind change management or training. If something we build is not used, it is because it was not good enough.

Our colleagues know what good looks like and will not use something worse than what they think they could build themselves in an afternoon. So we ship things people genuinely want, and the foundations arrive with them. That constraint does not go away.

The mandate is also larger than the team. The part no individual can do for themselves is the infrastructure, the access model and the architecture underneath, and getting that right across a company this size is the actual work. It does not come with a specification.

Responsibilities

• You will take broad ownership of how AI works inside Legora and of the platforms we build to make it work.
• Build internal agents, tools and platforms, and treat them as products rather than projects. Quality, reliability and whether they actually serve the business are yours, not someone else's
• Take a broad goal, work out what is actually required, and break it into the work yourself
• Own what you build end to end, from the architecture through to whether people use it and it holds up in production
• Shape what we should build and in what order, and argue for it
• Design the foundations: knowledge architecture, access and permissions, evaluation and monitoring, the guardrails that scale with risk
• Work directly with the people who will use what you build, across the whole company, including the parts furthest from engineering
• Who we are looking for
• Strong engineering fundamentals. You build production systems, not prototypes that need someone else to finish them
• Real depth with LLM-based systems. Agents, retrieval, evaluation, tool use. You know where these systems break and you design for it
• Ownership by instinct. You do not wait for a specification. When the requirement is unclear or wrong, you say so and propose something better
• Three kinds of understanding at once. Technical, domain and business. You can hold a conversation about architecture and a conversation about what the business actually needs, and connect them
• Openness. You take feedback, build on other people's ideas, change your mind when the evidence moves, and push for the strongest outcome rather than the one you proposed first
• Comfort with ambiguity. New team, fast growth, decisions that get revisited as we learn. That should sound appealing rather than annoying
• TypeScript. It's what we work in, and where our shared patterns live
• No aversion to infrastructure. We own ours, so Terraform and cloud providers are part of the work rather than someone else's problem
• You work with code agents daily. Not as an experiment, as how you build
• Legora is an Equal Opportunity Employer
• At Legora, we believe great teams are built on diversity of thought and experience. We’re proud to be an equal opportunity employer and committed to creating an inclusive, high-performance culture where everyone can do their best work. We welcome people of all backgrounds and don’t discriminate based on race, color, religion, national origin, gender, gender identity or expression, sexual orientation, age, disability, veteran status, or any other characteristic protected by law.