Company Overview
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.
We 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. Eve’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.
Our vision is simple yet transformative: enable every firm to operate at its highest potential through the power of AI.
Why Join Eve:
This 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.
When 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. You’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.
A 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. The 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.
This is a ground-floor opportunity. Eve’s support team is growing, with AI agent augmentation actively rolling out. You’ll help build the playbook at a fast-growing, Series B legal AI company backed by Spark Capital, a16z, Menlo Ventures, and Lightspeed — not maintain someone else’s
What You Will Accomplish:
Investigate AI Output Quality: When customers report issues with AI-generated legal documents, you investigate. You’ll use AI observability tooling to trace model inputs, outputs, and reasoning. You’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. You clearly communicate your findings to non-technical legal professionals.
Diagnose Technical Issues: Troubleshoot cloud storage sync failures (SharePoint, OneDrive, Dropbox), document formatting and export issues, file handling errors, integration configuration problems, and processing performance issues. Resolve what you can independently and escalate what you can’t with full diagnostic evidence.
Deliver Engineering-Ready Escalations: Every escalation you send to engineering includes an issue summary, trace logs, verified reproduction steps, document context, and business impact assessment. You set the quality bar for how support communicates with engineering.
Operate with Speed: Respond to customer support tickets within SLA. Prioritize ruthlessly. Manage multiple threads without dropping context.
Build the Support Infrastructure: Write SOPs, troubleshooting runbooks, and knowledge base articles. Contribute to our AI agent rollout by optimizing content for AI consumption. Help build the onboarding program for future support engineers. You are joining a team that is actively building its processes, not maintaining them.
Build with AI: Use AI tools daily to accelerate support workflows — drafting responses, analyzing ticket patterns, and diagnosing product behavior. Help shape how Eve deploys AI agents for first-touch triage and self-service resolution. Define what AI-native support looks like in legal tech.
What We Are Looking For:
AI Debugging Ability: You can investigate why an AI-generated document produced an unexpected result. You’re comfortable navigating AI observability and tracing tooling to understand model behavior. You can distinguish between a retrieval failure, a prompt issue, and a data ingestion problem — and explain the difference to a paralegal.
Technical Depth: You can read logs, trace API calls, debug OAuth token expirations, diagnose cloud storage sync failures, and reason about what’s happening under the hood of a SaaS product. You don’t need to be a software engineer, but you think like one when troubleshooting.
Structured Escalation Discipline: You document your work with precision. Your bug reports include trace logs, reproduction steps, relevant context, and a clear classification of the issue type. Engineering can pick up your escalation and start working immediately without asking follow-up questions.
Exceptional Communication: You can explain complex technical and AI-specific issues to attorneys who don’t care about your stack. You write clearly, concisely, and with empathy. You know when to simplify and when to be precise.
Ownership Mentality: You take personal responsibility for customer outcomes. You follow through until the problem is solved, not just escalated. You don’t wait to be told what to do.
You Will Thrive in This Role If You Have:
3+ years in a technical support, support engineering, or technical customer-facing role at a SaaS company
Experience supporting AI-powered or ML-driven products, with exposure to LLM observability or evaluation platforms
Background in legal technology, law firm IT operations, or professional services software
Familiarity with APIs, webhooks, OAuth, and integration debugging — especially cloud storage integrations (SharePoint, OneDrive, Dropbox)
Experience writing scripts (Python, JS) to automate support workflows or analyze data
Comfort with SQL for querying logs or data analysis
Understanding of prompt engineering concepts, retrieval-augmented generation (RAG), and LLM behavior patterns
History of contributing to SOPs, runbooks, knowledge bases, or internal tooling that materially improved team performance
Ability to work independently in a remote environment while collaborating effectively across team
