Director of Automation Engineering

About Huzzle

At Huzzle, we connect high‑performing professionals with global companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries like SaaS, Mar Tech, Fin Tech, and EdTech. We match top talent to full‑time remote roles where they are hired directly into client teams and receive ongoing support from Huzzle.

Role Type: Full‑time
Engagement: Independent Contractor

We're hiring a VP of Automation Engineering for a senior, hands‑on leadership role at the intersection of automation architecture, product engineering, and AI systems
. This is not a traditional management‑only role. You will operate as a technical leader who still ships code, designs systems, manages engineers, and partners directly with the founder on strategy. You will own and scale the automation infrastructure that powers delivery across multiple clients while also building internal and external products that turn operational know‑how into software. This role is ideal for someone with deep n8n
, JavaScript/Type Script ,
Node.js
, and Claude Code / LLM systems experience who has previously built automation infrastructure in a fast‑scaling startup, agency, or services environment.

• Automation Architecture & Infrastructure
  • Own the company’s end‑to‑end automation ecosystem, including workflow design, orchestration, monitoring, versioning, and scaling.
  • Build reliable, queue‑based and event‑driven automation systems that can support increasing client complexity without breaking under load.
  • Architect multi‑client automation infrastructure that supports different workflows, channels, cadences, and configurations across shared systems.
  • Design and maintain integrations across tools such as n8n, Clay, Airtable, Slack, Hub Spot, Email Bison, Hey Reach, and other operational platforms.
  • Implement robust error handling, alerting, and self‑healing workflows to improve reliability and reduce downtime.
  • Establish scalable standards for workflow documentation, deployment, credential management, and system governance.
• Product Development
  • Build internal products that transform operating processes into repeatable software, including dashboards, reporting tools, signal engines, and AI‑powered workflow systems.
  • Lead the full product engineering lifecycle from architecture and implementation through testing and deployment.
  • Develop client‑facing tools and automation products that extend the company’s value beyond services.
  • Set best practices for code quality, documentation, CI/CD, review processes, and release management.
• AI Systems & Intelligence Layer
  • Design and deploy production‑grade AI systems using Claude, OpenAI, and other LLM infrastructure.
  • Build intelligent workflows for classification, generation, summarization, decision support, and operational automation.
  • Determine where AI adds leverage versus where deterministic systems are the better architectural choice.
  • Improve the quality and reliability of AI systems through prompt design, evaluation, validation layers, fallback logic, and cost‑aware implementation.
• Team Leadership & Technical Direction
  • Build, mentor, and manage a growing automation engineering team.
  • Set engineering priorities, run sprint planning and retrospectives, and establish a high‑performance delivery culture.
  • Partner directly with the CEO/Founder as a senior technical counterpart on roadmap, systems design, and build‑vs‑buy decisions.
  • Help shape the long‑term technical organization, with clear progression toward a CTO‑level leadership path.

• Non‑Negotiable
  • Deep production‑level experience with n8n, including complex workflows, webhook architectures, credentials, execution logic, error handling, and workflow scalability.
  • Strong full‑stack development skills in JavaScript/Type Script, including Node.js backend systems and modern frontend development such as React or equivalent.
  • Experience managing engineering teams of 3+ people while remaining actively hands‑on in production code.
  • Proven experience building and maintaining AI/LLM systems in production, including model integration, prompt workflows, output validation,…