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# Senior AI Engineer

- **Company:** AnvilEight
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £36,000.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Databases, Data Transformation, JSON, Python (Programming Language), PostgreSQL, OAuth, Queueing Systems, Standard Sql, SQL Databases, Data Ingestion, Large Language Models, Prompt Engineering, Zapier, No-code Tools, Restful APIs, Webhooks, Docker
- **Published:** June 29, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=bb6555f4f5719966

## About the Role

Do you have experience in SQL?, Do you have a Master's degree?, 3+ years building automations and integrations, with hands-on experience in n8n and/or Make.com (Zapier a plus);
Solid Python for scripting, API integration and data transformation;
Strong SQL and relational-database skills (PostgreSQL preferred) - querying, joins and schema design;
Comfortable with REST APIs, webhooks, JSON and OAuth / authentication flows;
Practical experience integrating LLM / AI APIs (OpenAI or similar) into real workflows;
Understanding of error handling, idempotency, rate limits and observability in automations;
Bonus: Docker, vector databases / RAG, message queues, and JavaScript for n8n Function nodes;
Clear English and the ability to turn fuzzy business needs into reliable automated processes.

## Description

We're hiring a Senior AI Engineer to design and ship
automation that connects our tools, data and AI models. You'll build reliable
workflows in n8n and Make.com, back them with Python services and databases, and
wire in large language models to automate real business processes end-to-end -
from data ingestion to action. This is a hands-on, high-ownership role: you'll
turn fuzzy business needs into dependable automated systems and own the platform
they run on.

What you'll do

Design, build and maintain automation workflows in n8n and Make.com;
Integrate third-party APIs, webhooks and internal services into reliable end-to-end pipelines;
Write Python services, glue code and scheduled jobs that extend what no-code tools can do on their own;
Model, store and query data in SQL databases that back the automations;
Integrate LLM / AI APIs - prompt design, retrieval-augmented generation (RAG) and structured extraction - to automate real business tasks;
Add monitoring, error handling, retries and alerting so workflows run dependably in production;
Document the platform and own it as it grows.


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