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Advise lawyers and legal teams across EMEA on adopting Relativity’s AI products. Build customer relationships, support pre-sales demonstrations, enable post-sales onboarding and training, guide legal workflow transformation, and provide product feedback. Translate AI capabilities into practical legal use cases while partnering with sales, customer success, product, marketing, and engineering teams.

Own and grow a portfolio of major law firm accounts, driving retention, renewals, expansions, and strategic relationships with senior legal stakeholders. Lead complex negotiations, coordinate cross-functional account teams, identify competitive risks, and advise sales leadership on segment strategy. Represent the company at industry events, build executive networks, mentor Account Executives, and contribute to strategic initiatives. The role requires enterprise SaaS sales expertise, legal technology knowledge, technical fluency in AI and databases, executive presence, and regular travel.

Build and own production AI agents end to end, from tool and prompt design through evaluation, frontend experiences, deployment, monitoring, and continuous improvement. Develop full-stack services and shared AI infrastructure, debug retrieval and model issues, measure production performance, contribute to architecture and documentation, review code, mentor engineers, and collaborate with product, design, founders, and customers.

Supports partner-focused sales through technical consulting, product demonstrations, proof-of-concept management, proposals, risk assessments, and workflow assistance. Serves as a Relativity subject matter expert, evangelist, and liaison across sales, product, and partnership teams. Develops partner enablement materials, communicates customer feedback, maintains product and security expertise, mentors junior team members, and supports account growth. The role requires extensive SaaS and sales engineering experience, Relativity certifications, strong communication skills, and 25% travel.

Build and maintain full-stack AI features for Gavel, including agent tools, prompts, context, APIs, services, Word add-ins, and web applications. Develop evaluations, feature-flagged deployments, tests, and reliability improvements for agentic systems. Collaborate with senior engineers through pairing and code reviews while progressively taking ownership of ambiguous, end-to-end AI engineering problems.

Build and own production AI agents end to end, including tools, prompts, retrieval, evaluations, backend services, and Word or web interfaces. Ship cloud-native features, maintain evaluation and observability systems, debug model and retrieval issues, and contribute to reliable infrastructure. Collaborate with founders, product, design, customers, and engineers while mentoring teammates and driving continuous production improvements.

Leads end-to-end development of AI agent capabilities, including architecture, orchestration, retrieval, evaluation, Word and web experiences, deployment, monitoring, and quality standards. Codes approximately half the time while owning technical roadmaps, release decisions, cross-team platform and security collaboration, customer-informed prioritization, hiring, and mentorship of a small engineering team.

Lead the architecture and long-term roadmap for Relativity’s machine learning platform. Design scalable training, inference, monitoring, and ML operations systems; evaluate emerging technologies; improve model performance and cost efficiency through optimization techniques; and ensure secure, reliable AI services. Partner with product, program, and data science leaders, guide cross-functional initiatives, establish engineering standards, and mentor senior engineers across multiple teams.

Staff Engineer responsible for architecting and implementing secure, scalable full-stack cloud services processing petabytes of data. The role provides technical direction across frontend, backend, and data layers; resolves complex cross-organizational challenges; establishes engineering standards for performance, reliability, and security; aligns technical execution with product strategy; and mentors senior and lead engineers. The position requires extensive experience with cloud-native distributed systems, architecture, technical leadership, cross-team influence, and large-scale reliability.

Build and operate scalable, secure, distributed cloud services and data pipelines supporting AI-powered legal technology. Develop full-stack capabilities, improve platform throughput, latency, cost, and reliability, and contribute to APIs, model routing, durable workflows, observability, code reviews, incident response, and on-call support. Collaborate with product and engineering teams to safely deploy AI models across commercial and government cloud environments.