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The role focuses on managing eDiscovery projects, ensuring client satisfaction, and coordinating tasks across various stages of the EDRM Model.

Design, build, and deploy AI-driven features and intelligent agents using LLMs and GenAI. Integrate models via APIs and microservices, modernize automations with MCP servers and agentic frameworks, apply prompt engineering, ensure security/compliance, and document production-ready architectures and best practices.

Process, prepare, and quality-control electronic discovery data using proprietary litigation-support tools (Nuix, Relativity). Communicate project status, resolve or escalate issues, meet time-sensitive deadlines, and follow quality standards while investigating errors and improving processes.

Support senior client services by coordinating project execution for eDiscovery clients: translate client requirements into work requests, intake and prepare data, troubleshoot data issues, manage review platforms (Relativity/DMX), produce privilege logs and reports, monitor budgets, ensure shift handoffs, drive client satisfaction, and participate in process improvements.

Lead design and delivery of technical automation and integration solutions for legal clients. Perform business requirements analysis, solution architecture, implementation, troubleshooting, documentation, custom tool development, project management, and client relationship building.

Lead requirements, design, configuration, and validation of AI/GenAI capabilities within a CLM platform. Collaborate with legal, procurement, and data science teams to implement NLP/GenAI features (clause extraction, risk scoring, contract generation), manage testing/UAT, optimize templates and clause libraries, and deliver reporting and change management to drive adoption.

Perform daily quality assurance reviews of contact center CSR calls, provide QA scores and feedback to leads, resolve complex QA disputes, and assist the QA Supervisor with weekly calibration sessions. Support staff development, training, quality control, and prepare QA documentation.

Lead client-facing project delivery for e-discovery engagements: manage multiple projects, coordinate schedules and forecasts, maintain project status and quality, drive client satisfaction, escalate issues, oversee financial/billing reviews, and provide leadership to clients and internal teams.

Supervise and manage a claims operations team to ensure accurate, timely claims processing. Set expectations, train staff, manage workflow and performance, perform quality assurance and risk analysis, handle escalations and audits, collaborate with Client Services and Data Services, and improve processes and documentation to drive operational excellence.

Advise clients on antitrust eDiscovery compliance using machine learning and generative AI. Build and validate TAR/AI models (Epiq AI, Relativity, Reveal, Brainspace), craft LLM prompts, draft defensible protocols, train/transfer workflows to review teams, and support client-facing, pre-sales, and thought-leadership activities. Must manage multiple projects and meet deadline-driven schedules.