(Applied) AI Engineer

About the role

We're building the self-maintaining source of truth for the AI-native company, the context repository that keeps company knowledge structured, up-to-date, permission-aware, and ready for every AI agent.

That takes people who are exceptionally talented, obsessed by the vision, and set on doing the best work of their lives. If that's you, read on.

THE OPPORTUNITY

You'll design and scale the backend that powers a company's brain, the logic that lets AI reason over live company knowledge instead of static data.

You'll own the architecture behind sync and retrieval: turning unstructured information from every data source into a structured, versioned, queryable context repository. Your work defines how AI systems across our customers' organizations reach relevant, up-to-date, permission-aware context in real time.

We're already live with 15+ design partners and launching v1 in Q3 2026. This is the rare moment where the product, the architecture, and the category are still yours to shape. We think of Qontext as a once-in-a-lifetime opportunity, and we hire people who feel the same.

WHAT YOU’LL DO

- Design and implement the core backend logic of the context repository

- Build and optimize the sync, turning raw data source data into structured, graph-based context

- Develop high-performance retrieval and ranking, combining hybrid search, rule-based logic, and identity resolution

- Productize complex logic through clean APIs and modular components (MCP, CLI, API, etc.)

- Build evaluation and experimentation frameworks that continuously raise contextual accuracy

YOU’LL THRIVE HERE IF YOU…

- Love distributed systems and high-complexity logic problems

- Are fluent in TypeScript or Python and have an eye for clean, scalable architecture

- Turn research and theory into production-grade product

- Have a bias for ownership and thrive in fast-paced, early-stage environments

- Are endlessly curious and pragmatic, and care about making AI truly useful

WHY JOIN US

- Challenge: A genuinely hard intellectual and systems problem

- Cutting edge: Turning the latest research into a product used at scale

- Mission: Building the infrastructure for the next generation of work

- Impact: Shape the company and architecture from day one

- Ownership: Competitive salary plus meaningful early equity

- Culture: Deep-tech mindset, transparency, radical candor and fast execution

PROCESS

1. Get to know each other · 30 min

2. Chat with co-founder(s) · 30 min

3. Technical interview · 1h

4. Take-home case · 3h

5. Case discussion · 1h

6. Offer

PRACTICAL INFO

- Location: Berlin

- Start date: ASAP