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Legora is an AI-native legal workspace trusted by 2,100+ customers across 80+ countries, including major law firms like Cleary Gottlieb, Goodwin, and Linklaters. The company has scaled to $200M+ ARR and operates teams across Europe, North America, and APAC.
As an AI Automation & Enablement Engineer, you will raise the baseline of AI fluency across Legora and help colleagues develop confidence and skills with AI and automation. You'll work as an embedded engineering partner to internal teams, combining hands-on building with practical teaching to turn promising experiments into reliable workflows.
Key responsibilities include:
- Spend time with employees across functions to understand tasks and identify opportunities to improve quality, reduce manual effort, or remove delays
- Work alongside colleagues on real tasks, helping them provide useful context, break down problems, and evaluate outputs
- Build automations and internal tools using AI coding tools, scripts, APIs, agents, and workflow platforms
- Run hands-on sessions and office hours to raise AI fluency and help employees build independent skills
- Identify approaches that work and make them easy to reuse across teams
- Evaluate new AI capabilities and explain tradeoffs in usefulness, reliability, cost, and adoption ease
- Match AI models to tasks, comparing quality, speed, and cost to improve productivity and reduce unnecessary spend
- Test outputs and verify actions in connected systems, working with IT and Security on permissions and monitoring
- Follow up after launch, resolve failures, and improve solutions based on actual usage
- Track changes in manual effort, turnaround time, errors, output quality, and sustained adoption
You'll work with tools such as Claude, Claude Code, ChatGPT, Codex, Cursor, and other AI and automation platforms.
Requirements:
- Demonstrated experience building automations, integrations, or internal tools that other people use, with ability to explain the problem, decisions, and resulting impact
- Active AI power-user with substantive experience using Claude, ChatGPT, Codex, or Cursor; understanding of their limitations and when AI, conventional automation, or simpler processes are appropriate
- Ability to match models to tasks, balancing quality, speed, and cost
- Clear, patient teaching skills; comfort working with people at different confidence levels and explaining technical ideas simply
- Curiosity about how work gets done; ability to ask useful questions, find underlying problems, and translate vague requests into practical next steps
- Thoughtful approach to reliability and access; ability to verify results, handle sensitive information carefully, and know when actions need human review
- Accountability for documentation, maintenance, and adoption after launch; focus on whether work delivers value
Nice to have:
- Experience building internal AI tools or delivering practical AI enablement programs
- Experience connecting agents to business applications, APIs, and knowledge sources
- Experience evaluating AI outputs, testing workflows, or monitoring integrations
- Examples of tools, guides, or workshops that helped colleagues adopt better ways of working
