AI Enablement Engineer

Posted on:

July 14, 2025

Responsibilities

What you’ll do:

Co-Design & Build: Partner with cross functional department leaders to identify and scope high impact automation opportunities across the business.
Implement Internal Solutions: Take the lead on hands-on development of internal tools and workflows using a modern stack including N8N, and the Google Cloud Platform.
Execute Key Projects: Your first major project will be to ship a knowledge retrieval platform, and a core automations workflow that sits across functions to maximise efficiency across the team.
Develop APIs & Integrations: Build and maintain the crucial API connections that allow our internal systems (like Notion, Slack, Hubspot, Stripe) to communicate and share data seamlessly.
Manage AI Enablement Infrastructure: Deploy and manage the specific AI and automation services on our Google Cloud Platform, including Vertex AI for model integration and vector databases for internal knowledge retrieval.
Collaborate & Support: Act as a technical expert and partner to our Core Product Engineering team, ensuring the solutions you build are secure, scalable, and well-integrated into our existing infrastructure.

Job requirements

What we will look for:

Expert Communication: As this is a cross functional role, that sits parrallel to our core engineering team you will need to be an expert communicator.
A Passion for Enablement: A genuine interest in making others' work-lives better and a knack for understanding internal business processes.
Collaborative Mindset: A history of working effectively with other engineering teams and business stakeholders.
AI and technical curiosity: You will have proved experience of building workflows, and exploring the new tools. With an understanding of the architecture of LLM and agentic orchestration.

Preferred skills:

Google Cloud Platform (GCP) Expertise: Proven, hands-on experience deploying and managing applications and services on GCP, particularly with serverless and AI services (Cloud Functions, Vertex AI, etc.).
Strong API Development Skills: Demonstrable experience designing, building, and maintaining RESTful APIs, using languages like Python or Node.js.
Applied AI & LLM Experience: Practical experience integrating with LLM APIs (e.g., Google Gemini, OpenAI) and an understanding of core concepts like RAG, Model Context Protocol, and prompt engineering for business process use cases.
Vector Database Knowledge: A solid understanding of what vector databases are and how they can be applied to internal knowledge management.
Low-Code/Workflow Automation Experience: Direct, hands-on experience with tools No-code tools like N8N, Zapier, or Make is a significant advantage.
Agentic Frameworks: Familiarity with building autonomous agents using platforms like one of the above no-code tools, or Googles Vertex AI Agent Builder.
SaaS Integration Experience: You've worked on connecting the APIs of modern business tools like Notion, Slack, Hubspot, and Stripe.

Job description