Technology Consultant - Remote in London

At Epiq, your work contributes to complex, global legal outcomes. You’ll join a values‑driven community where integrity guides decisions, relentless service sets the bar, and we thrive on big challenges together. Enabled by modern platforms and AI, you’ll do the most meaningful work of your career and see your impact at scale.

The Advanced Technologies Consultant supports clients in the effective, defensible, and commercially practical use of analytics, machine learning, and generative AI across eDiscovery, document review, investigations, early case assessment, privilege review, regulatory response, and related legal data workflows.

Working closely with Advanced Technologies leadership and cross-functional teams across Client Services, Document Review Services, Sales, Operations, and Information Technology, the Consultant serves as a client-facing subject matter expert. The role is responsible for helping clients identify appropriate workflows, configure and apply advanced technology solutions, explain technical and statistical concepts in clear business and legal terms, and ensure that projects are delivered efficiently, defensibly, and in line with client objectives.

This role is well suited to someone with strong eDiscovery experience, a consultative mindset, and a practical understanding of document review. A legal background, litigation support experience, or prior review management experience would be particularly valuable, as the Consultant will often need to bridge legal strategy, review execution, technology configuration, and client-facing advice.

The successful candidate must be comfortable managing multiple projects concurrently, working independently through ambiguity, collaborating across teams, and occasionally supporting urgent project needs outside standard business hours.

Key Responsibilities

• Serve as a subject matter expert on the use of advanced analytics, technology-assisted review, predictive coding, machine learning, and generative AI in eDiscovery and document review workflows.
• Consult with clients and internal stakeholders to understand matter objectives, legal and review requirements, data challenges, timelines, and desired outcomes.
• Design and recommend defensible workflows using tools such as TAR 1.0, TAR 2.0, active learning, AI-assisted classification, privilege identification, early case assessment, data reduction, and investigative analytics.
• Build, manage, validate, and refine analytics and AI models across platforms such as Relativity, Epiq AI, Reveal AI, and other advanced review or analytics platforms.
• Develop and refine prompts, instructions, classification criteria, and model guidance for generative AI and LLM-enabled tools, with a focus on consistency, quality, defensibility, and practical review outcomes.
• Advise clients and internal teams on appropriate use cases, limitations, risks, defensibility considerations, and quality control measures for AI-enabled review workflows.
• Explain statistical concepts, validation methodologies, sampling approaches, model performance, and review metrics to audiences with varying levels of technical, legal, and operational knowledge.
• Demonstrate a strong understanding of the full eDiscovery lifecycle, including data assessment, culling, review strategy, privilege workflows, production requirements, regulatory requests, and post-review analysis.
• Support privilege-related workflows, including privilege identification, common-name normalisation, privilege log support, and procedural guidance for review teams.
• Partner with Client Services, Document Review Services, Operations, Sales, and Technology teams to ensure successful delivery of assigned projects.
• Document key project decisions, workflows, assumptions, and lessons learned, and transfer knowledge to review and client service teams to support repeatable and scalable delivery.
• Oversee or guide the work of analysts, associate consultants, review managers, or other project resources where appropriate.
• Track project successes, risks, lessons learned, and client outcomes, and contribute to internal reporting as required.
• Mentor colleagues and help build internal knowledge of analytics, AI, TAR, and advanced review workflows.
• Maintain subject matter expertise through continuing education, platform certifications, market awareness, and active engagement with developments in eDiscovery, legal technology, analytics, AI, and generative AI.
• Support business development activities where needed, including demonstrations, client presentations, training sessions, pre-sales discussions, and thought leadership.

Minimum Qualifications

• Minimum of 5 years’ client-facing experience in eDiscovery, litigation support, legal technology, document review, investigations, regulatory response, or a related field.
• Practical experience with eDiscovery review platforms, including Relativity Server and/or RelativityOne, and general administration of document review databases.
• Experience using technology-assisted review, predictive coding, active learning, analytics, machine learning, or generative AI tools in an eDiscovery or legal data context.
• Strong understanding of the eDiscovery lifecycle, including data processing, review strategy, review management, quality control, privilege, production, and defensibility considerations.
• Strong written and verbal communication skills, with the ability to engage confidently with legal, technical, operational, and executive stakeholders.
• Proficiency with Microsoft 365, including Excel and other core productivity tools.
• Willingness to work flexibly when required by client demands, matter deadlines, productions, regulatory requests, or other urgent project needs.

Preferred Qualifications and Experience

• Legal qualification, litigation experience, or equivalent legal training.
• Prior experience as a review manager or in a similar role overseeing legal document review workflows.
• Advanced degree such as JD/LLB, MBA, MSc, or equivalent industry experience.
• Familiarity with tools such as Relativity Active Learning, Epiq AI, Reveal AI, or similar analytics and AI-enabled review platforms.
• Experience with privilege review workflows, privilege log preparation, common-name normalisation, legal issue coding, responsiveness review, confidentiality review, and quality control processes.
• Experience supporting investigations, early case assessment, antitrust / Second Request matters, regulatory responses, litigation reviews, or post-production analysis.
• Prompt engineering experience, including developing, testing, and refining prompts or instructions for tools such as Copilot, Claude, Gemini, Harvey, or other LLM-enabled platforms.
• Familiarity with Power BI, Python, SQL, data analytics, reporting, or dashboarding.
• Interest in legal technology innovation, AI adoption, defensible automation, and the practical application of emerging technologies to legal and review workflows.

Key Skills and Competencies

• Client consultation and stakeholder management
• eDiscovery and document review workflow design
• Technology-assisted review and predictive coding
• Generative AI and LLM-enabled review workflows
• Analytics model setup, validation, and interpretation
• Prompt development and refinement
• Privilege review and legal issue analysis
• Review management and quality control
• Statistical literacy and defensibility
• Technical communication and report writing
• Cross-functional collaboration
• Commercial awareness and solution design
• Mentoring, knowledge sharing, and internal enablement
• Adaptability, judgement, and practical problem solving

A successful Advanced Technologies Consultant will combine legal and review-domain understanding with strong technical aptitude and client-facing judgement. They will be able to understand the client’s substantive legal or investigative objective, identify the right technology-enabled workflow, explain the approach clearly, and drive delivery through collaboration with review, client service, technology, and sales teams. They will advise on how and when those tools should be used, where the risks are, how outputs should be validated, and how advanced technologies can improve quality, efficiency, consistency, and defensibility across the matter lifecycle.