We’re building the independent context layer for AI – a missing piece of infrastructure that allows every AI process in a company to act on relevant and up-to-date context.
We’re a fast-moving, well-funded team based in Berlin, backed by HV Capital, Zero Prime and the founders of n8n, neo4j, Cognigy, make.com, Celonis and Nabla.
In this role, you’ll architect and build the core logic that powers how a company’s brain operates – ensuring the Qontext platform provides high-performance, context-aware data to AI agents in real-time.
You’ll be responsible for the backend of our platform: from building complex data connectors and ingestion pipelines to designing the APIs that expose our platform to LLM-powered applications. You won't just be managing servers; you'll be writing the code that solves deep data-consistency and retrieval challenges.
Qontext is already being used by 10+ design partners, and we are aiming to launch v1 of our platform in Q2 2026. If you enjoy building scalable application logic from first principles and shipping products that define a new category, this role is for you.
What You’ll Do
Architect and develop robust backend services using TypeScript and Python that form the core of the Qontext intelligence layer.
Build and optimize data ingestion engines that interface with external APIs (e.g., HubSpot, Notion, Slack) to sync and transform data for AI consumption.
Design and implement scalable APIs and orchestration logic for our customer-specific knowledge graphs.
Collaborate on data modeling to ensure high-speed retrieval and relevance for RAG (Retrieval-Augmented Generation) workflows.
Write clean, maintainable, and highly-tested code that can scale from 10 design partners to thousands of enterprise users.
You’ll Thrive Here If You…
Love designing complex application logic and working with distributed systems (queues, caches, and microservices).
Are fluent in TypeScript and/or Python, with a deep understanding of asynchronous programming and API design.
Have a strong interest (or experience) in graph databases or vector stores and how they power the modern AI stack.
Value code quality and system reliability – you take pride in shipping features that don't break under load.
Thrive in an early-stage, low-ego, high-ownership environment where you have a direct seat at the product-design table.
Why Join Us
Challenge: Highly complex intellectual & logical challenge
Cutting Edge: Turning latest research into a product used by the masses
Mission: Build the foundational context infrastructure for AI processes
Impact: Shape the company and architecture from day one
Ownership: Competitive salary + meaningful early equity
Culture: Deep-tech mindset, transparency, radical candor and fast execution
Process
Get to know each other – 30 min
Technical interview – 30 min
Technical take-home case – 3 h
Case discussion – 45 min
Offer
Practical Info
Location: Berlin
Start date: ASAP
Type: Full-time
Compensation: €80k - €120k + equity package
Skills Required
- Proficiency in TypeScript and/or Python
- Experience with asynchronous programming and API design
- Knowledge of graph databases or vector stores
- Experience in distributed systems design
What We Do
Qontext builds the foundational context infrastructure for AI processes, acting as the context layer for AI applications.
