At Eve, we're redefining what's possible in legal technology. Our mission is to empower plaintiff law firms with AI-driven solutions that elevate how they operate, serve clients, and grow.
\nWe believe the future of law will be built by 'AI-Native Law Firms' , firms that are managed, scaled, and optimized by intelligent systems rather than manual processes and endless administrative work.
\nEve's technology augments the capabilities of attorneys across every stage of a case , from intake and document review to strategy and settlement , so they can focus on what truly matters: achieving the best outcomes for their clients.
\nOur vision is simple yet transformative: enable every firm to operate at its highest potential through the power of AI.
\nWhy Join Eve:
\nThis is not a traditional support role. Eve's Technical Support Engineers are technical problem solvers who work at the intersection of a cutting-edge AI product and the 850+ plaintiff law firms that depend on it.
\nWhen a paralegal reports that a medical chronology 'doesn't look right,' your job is to determine whether that's a retrieval issue, a data ingestion problem, a model behavior question, or user error.
\nYou'll investigate using AI observability tooling, document your findings with precision, and either resolve the issue or hand engineering a complete diagnostic they can act on immediately.
\nA significant portion of this role involves investigating AI output quality , understanding why the product generated what it did and whether the result is correct, incomplete, or wrong.
\nThe rest is split between diagnosing traditional technical issues (document formatting, cloud storage sync, integrations) and building the support infrastructure itself: writing SOPs, expanding the knowledge base, and helping shape our AI agent rollout.
\nWhat You Will Accomplish:
\nYou'll use AI observability tooling to trace model inputs, outputs, and reasoning.
\nYou'll verify claims against source documents and determine whether the issue is a retrieval failure, a data ingestion problem, a prompt issue, or expected model behavior.
\nYou clearly communicate your findings to non-technical legal professionals.
\nResolve what you can independently and escalate what you can't with full diagnostic evidence.
\nYou set the quality bar for how support communicates with engineering.
\nPrioritize ruthlessly.
\nManage multiple threads without dropping context.
\nContribute to our AI agent rollout by optimizing content for AI consumption.
\nHelp build the onboarding program for future support engineers.
\nYou are joining a team that is actively building its processes, not maintaining them.
\nHelp shape how Eve deploys AI agents for first-touch triage and self-service resolution.
\nDefine what AI-native support looks like in legal tech.
\nWhat We Are Looking For:
\nYou're comfortable navigating AI observability and tracing tooling to understand model behavior.
\nYou can distinguish between a retrieval failure, a prompt issue, and a data ingestion problem , and explain the difference to a paralegal.
\nYou don't need to be a software engineer, but you think like one when troubleshooting.
\nYour bug reports include trace logs, reproduction steps, relevant context, and a clear classification of the issue type.
\nEngineering can pick up your escalation and start working immediately without asking follow-up questions.
\nYou write clearly, concisely, and with empathy.
\nYou know when to simplify and when to be precise.
\nYou follow through until the problem is solved, not just escalated.
\nYou don't wait to be told what to do.
\nYou Will Thrive in This Role If You Have:
\nExperience supporting AI-powered or ML-driven products, with exposure to LLM observability or evaluation platforms
\nBackground in legal technology, law firm IT operations, or professional services software
\nFamiliarity with APIs, webhooks, OAuth, and integration debugging , especially cloud storage integrations (SharePoint, OneDrive, Dropbox)
\nExperience writing scripts (Python, JS) to automate support workflows or analyze data
\nComfort with SQL for querying logs or data analysis
\nUnderstanding of prompt engineering concepts, retrieval-augmented generation (RAG), and LLM behavior patterns
\nHistory of contributing to SOPs, runbooks, knowledge bases, or internal tooling that materially improved team performance
\nAbility to work independently in a remote environment while collaborating effectively across team
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_c6ad7239-e8e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Eve","sameAs":"https://www.eve.com/","logo":"https://logos.yubhub.co/eve.com.png"},"x-apply-url":"https://jobs.lever.co/Eve/8ee47c51-3480-4af6-8ab7-d8f22b7922e2","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AI Debugging","Technical Support","Cloud Storage Integrations","APIs","Webhooks","OAuth","Integration Debugging","SQL","Prompt Engineering","Retrieval-Augmented Generation","LLM Behavior Patterns"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:31:21.689Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"US"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI Debugging, Technical Support, Cloud Storage Integrations, APIs, Webhooks, OAuth, Integration Debugging, SQL, Prompt Engineering, Retrieval-Augmented Generation, LLM Behavior Patterns"}]}