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Legora

AI Marketing Engineer

New York City$188k–$231kfulltimemidAdded 1 month ago

About this role

Legora, an AI-native legal software platform, seeks an AI Marketing Engineer to redesign marketing workflows using AI agents. You'll partner with marketing leaders to build intelligent automation systems that replace manual processes, working across the full lifecycle from problem definition through deployment and iteration.

What you'll do

  • Design and deploy AI-native marketing workflows with human oversight and supervision
  • Lead end-to-end solutions from problem scoping and prompt engineering to integration and testing
  • Research and evaluate frontier AI models and agent frameworks for marketing use cases
  • Build integrations connecting AI agents to the marketing data stack
  • Evangelize AI capabilities across the broader marketing organization

What they're looking for

  • LLM and prompt engineering expertise
  • Agentic orchestration frameworks and workflow design
  • Marketing operations and automation background
  • Data stack integration and API connectivity
  • Problem-solving and process optimization mindset
  • Clear communication with non-technical stakeholders
  • Understanding of marketing business metrics and goals

Benefits

  • Competitive salary and comprehensive benefits package
  • Global collaboration across Europe, North America, and APAC
  • Union Square office with daily company-provided lunch
  • Work on meaningful projects impacting thousands of legal professionals
  • Opportunity to shape rapidly evolving AI landscape
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Legora

Legora builds an AI-powered platform designed to transform how enterprise legal teams and law firms operate. The company is hiring Forward Deployed Engineers to embed with clients and build integrations, and Legal Engineers who combine legal expertise with product knowledge to drive adoption and serve as strategic advisors to corporate legal departments.

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Likely interview questions

  • Walk us through a marketing automation or AI workflow you've built end-to-end—what problem did it solve, what tools did you use, and how did you measure success?
  • Describe your experience with LLMs and prompt engineering. Have you built or deployed agents, and how did you handle ensuring reliable outputs?
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