Lead AI Automation Engineer - Europe (Hybrid)

Orix Digi

Harrow

Hybrid

GBP 90,000 - 130,000

Full time

21 hours ago
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Job summary

Orix Digi is seeking a Lead AI Automation Engineer to own AI workflow automation and orchestration outcomes for Europe, translating demand signals into measurable impact. Based in London with hybrid work, you will drive KPI governance, weekly optimization, and cross-functional collaboration to improve execution quality and speed.

You will lead end-to-end delivery, translate goals into KPI trees, run experiments, and document learnings for scalable decisions.

Qualifications

  • 7–10 years of experience in AI workflow automation and orchestration.
  • Hands-on with OpenAI, n8n, API integrations.
  • Strong communication and stakeholder management in cross-functional environments.
  • Data-informed decision making with KPI and performance analysis.
  • Demonstrated ownership mindset with the ability to execute against deadlines.

Responsibilities

  • Own end-to-end delivery for AI Automation Engineer initiatives, from planning through execution and optimization.
  • Translate business goals into KPI trees, sprint priorities, and measurable weekly actions.
  • Run structured experiments and document performance learnings for scaling decisions.
  • Collaborate with adjacent teams to align creative, technical, and operational dependencies.
  • Maintain QA discipline, reporting clarity, and leadership-ready status updates.

Skills

AI workflow
Orchestration
Cross-functional
KPI analysis
OpenAI
n8n
API integrations

Tools

OpenAI
n8n
API integrations

Job description

Orix Digi is seeking a Lead AI Automation Engineer to own AI workflow automation and orchestration outcomes for Europe, translating demand signals into measurable impact. Based in London with hybrid work, you will drive KPI governance, weekly optimization, and cross-functional collaboration to improve execution quality and speed.

You will lead end-to-end delivery, translate goals into KPI trees, run experiments, and document learnings for scalable decisions.

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