Staff Core Platform Engineer

present of AI; Berlin; Hybrid; EUR 120,000 - 170,000; Full time

Job summary

n8n is seeking a senior architecture lead to own the core of our product: how workflows run, queues scale across workers, and how data is stored for reliability at scale. You will shape the frontend platform and guided by strong designs, leading multi-team changes and designing for failure modes.

You will work close to the infrastructure that powers AI agent workflows, with emphasis on durable execution, task distribution, and safe operation for many customers.

Qualifications

• Led multi-team technical changes with cross-team impact.
• Thoughtful about failures and trade-offs in system design.
• Deep experience with TypeScript and Node.js backend.

Responsibilities

• Oversee core architecture of workflows, queuing, data storage, and scaling of the platform.
• Guide engineering teams through RFCs and design reviews.
• Draft proposals and align multiple teams on long-term architecture decisions.

Skills

TypeScript

Node.js

Distributed systems

Idempotency

Job description

This is a senior architecture role covering the core of the product: how workflows run, how work is queued and spread across workers, how data is stored and scaled, and how the frontend platform is built on. A strong candidate has led multi-team technical changes before, thinks carefully about failures and trade-offs, and has deep TypeScript and Node.js backend experience. Writing clear proposals and guiding other engineers matters as much as writing code.

How it fits the AI era

n8n is a place where people build AI agents and automations, so the platform underneath has to run long, unpredictable, and failure-prone workloads reliably. AI tools can speed up code writing and exploring options, but the judgment on correctness, isolation, and long-term design choices stays with people. Deciding which trade-offs to accept and getting many teams to agree on them remains human work.

How it builds AI experience

The role offers close exposure to the infrastructure that AI agent workflows depend on, such as durable execution, task distribution, and running work safely for many customers at once. To build relevant experience, try n8n, build an agent workflow, and study where it could break or slow down at scale. Understanding what agent workloads demand from a workflow engine is a strong base for this work.

Worth showing

• Distributed systems and idempotency
• TypeScript and Node.js backends
• Database scaling and migrations
• RFCs and design reviews

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About N8n