Legora AI Automation & Enablement Engineer partnering with internal teams at Legora to build AI-powered workflows and raise AI fluency. Responsible for identifying automation opportunities and creating practical AI solutions.
Responsibilities
We want every employee at Legora to get more from AI. As an AI Automation & Enablement Engineer, your mission is to raise the baseline of AI fluency across the company and help colleagues have their own aha moments with AI and automation.
You’ll work as an embedded engineering partner to internal teams: understand how people work, build useful solutions alongside them and help them develop the confidence and skills to use AI independently. You’ll combine hands-on building with practical teaching, turning promising experiments into reliable workflows that people use every day.
You’ll work with tools such as Claude and Claude Code, OpenAI’s ChatGPT and Codex, Cursor, and other AI and automation platforms. You’ll choose the right approach for the problem, from a better way to use an existing tool to an integration or internal application.
Find work worth improving: Spend time with employees across functions to understand their tasks and identify opportunities to improve quality, reduce manual effort or remove delays.
Create practical "aha" moments: Work alongside colleagues on their real tasks. Help them provide useful context, break down problems, evaluate outputs and see where AI can meaningfully improve their work.
Build automations and internal tools: Use AI coding tools, scripts, APIs, agents and workflow platforms to take useful ideas through testing, rollout and ongoing use.
Raise AI fluency: Run hands-on sessions and office hours, create clear examples and reusable workflows, and help employees build skills they can apply independently.
Turn individual wins into shared practice: Identify approaches that work, make them easy to reuse and help teams develop their own confident AI practitioners.
Choose tools thoughtfully: Evaluate new capabilities and explain the tradeoffs in usefulness, reliability, cost and ease of adoption. Simplify the process before automating it.
Optimize model selection and spend: Match models to the task, comparing quality, speed and cost to improve employee productivity and reduce unnecessary AI spend. Help teams understand when a faster, lower-cost model is sufficient and when a more capable model justifies the additional cost.
Make workflows dependable: Test outputs and verify actions in connected systems. Work with IT, Security and system owners on appropriate permissions, human review, monitoring and recovery steps.
Own adoption and improvement: Follow up after launch, resolve failures and improve what you build based on how people actually use it.
Qualification
A practical builderAn active AI power-userA clearCurious about how work gets doneThoughtful about reliability and accessAccountable after launchExperience evaluating AI outputsExamples of toolsWhat’s in it for youVisible impactRoom to buildGlobal collaboration
Required
A practical builder: You’ve built automations, integrations or internal tools that other people use. You can explain the problem, your decisions and the resulting impact.
An active AI power-user: You use tools such as Claude, ChatGPT, Codex or Cursor for substantive work. You understand their limitations and can judge when AI, conventional automation or a simpler process is appropriate. You can match models to the task, balancing quality, speed and cost to improve productivity and reduce unnecessary spend.
A clear, patient teacher: You enjoy working with people at different levels of confidence, explain technical ideas simply and help others solve problems themselves.
Curious about how work gets done: You ask useful questions, find the underlying problem and translate a vague request into a practical next step.
Thoughtful about reliability and access: You verify results, handle sensitive information carefully and know when an action needs human review or a system owner’s input.
Accountable after launch: You follow through on documentation, maintenance and adoption, and stay focused on whether the work is delivering value.
Preferred
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 a better way of working.
What’s in it for you
Visible impact: Help employees across Legora do better work and build lasting confidence with AI.
Room to build: Work directly with the people using your solutions and see their feedback shape what you deliver.
Global collaboration: Partner with colleagues across Europe, APAC and North America.
