Legal Engineer

Position: Legal Knowledge Engineer
Our Practice Solutions team leads the Firm’s innovation initiatives, supporting our lawyers in client delivery excellence. The team has deep expertise in working with established and emerging technologies, data analytics and data science, knowledge solutions and process re-engineering. The Practice Solutions team works with our lawyers to identify innovative solutions to support our clients. Through fostering a Firmwide culture of innovation, we encourage our lawyers to think creatively about how to deliver the best value to our clients and we ensure that White & Case remains at the forefront of advancements in the legal industry.

Position Summary We are looking for a Legal Knowledge Engineer to help ensure we drive value from the systems that hold, classify and surface our knowledge. You will use AI to enhance the firm's knowledge, and onboard teams to the firm's knowledge systems. In practice this makes the role part builder, part governor and part translator: building the classification and metadata that make content usable, governing the quality of that work as it scales across teams, and translating what fee earners need into changes the firm's knowledge and AI systems can actually deliver.

This role requires a dual skillset. It calls for someone comfortable working hands-on with taxonomies, metadata and AI tooling, but equally comfortable working with lawyers to understand how they work and where knowledge is created, lost or duplicated. The firm is consolidating its knowledge estate and connecting that knowledge to the tools lawyers use day to day - this role is central to making that happen.

The White and Case knowledge strategy rests on four pillars: clean data, a single system, governed AI assets, and a culture of sharing. Our Legal Knowledge Engineer is the operational role that carries much of that work into individual practices. You will support the implementation of the firm's strategic knowledge system, partnering with PSLs/Knowledge Lawyers and supporting roles to drive value from our knowledge.

A primary focus will be on automated classification at scale, the classification playbook resourcing model, and onboarding teams to the new systems.

Duties and Responsibilities Classification, Metadata and Enrichment (Pillar: Clean Up Data)
Build classification capabilities for teams that need significant support, taking a lead role in their design and working directly with lawyers to validate outputs before they are relied upon Provide a governance layer over classification work carried out by PSLs and other domain experts, so that skills are built consistently, produce good results, and are measured properly rather than assumed to work.

Design and run classification at scale so the firm can handle the large majority of tagging and profiling centrally, with domain experts validating the output rather than manually re-profiling document by document.

Use AI to enhance the firm's knowledge: reducing the burden of long classification forms, producing draft profiles for PSL review, and enriching content with the metadata that makes it findable and useful.

Define practice-specific metadata with each team, including their legal topics, document types and the data points that matter to how they practise.

Bring rigour to how classification quality is assessed, including the use of gold sets, calibration and review feedback loops, so confidence in a skill's output is earned from evidence rather than asserted.

Requirements and Practice Engagement (Pillar: Single System)
Work with fee earners and practice groups to understand their knowledge requirements across content, features and data, ensuring those needs inform the firm’s knowledge strategy and system development.

Act as a point of contact…