🛸 AI Product Engineer - Backend
Wir glauben an Arbeit, die allen im Team Freude bereitet und geben alles, damit Projektchaos der Vergangenheit angehört. Mit awork stellen wir das Projektmanagement-Tool bereit, das Agenturen brauchen, um Großartiges zu erreichen.
Unsere Kunden planen damit die besten Werbekampagnen der Welt, organisieren Wahlen und drehen Kinofilme. Wir kriegen fast ein bisschen Pipi in den Augen vor Stolz, wenn wir so darüber nachdenken.
Wir freuen uns, wenn du ein Teil davon werden willst.

We believe in work that brings joy to everyone on the team and do everything to make project chaos a thing of the past. With awork, we provide the project management tool that agencies need to achieve great things. Our customers use it to plan the world's best advertising campaigns, organise elections, and produce feature films. We get a little teary-eyed with pride when we think about it. We'd be thrilled if you want to become part of it.
We launched awork AI assistant early, a fully capable assistant built directly into our product. Now we're going further: agents that handle real creative and strategic work inside awork, right alongside our customers' teams.
You'd be the second engineer on this. Working closely with Nils (Founder) and Sebastian (CTO) to build, ship, and iterate on AI agent features for 10,000+ agency teams. This isn't a chatbot in a corner. It's shaping how agencies work in the AI-first world.
👉 This is a backend-heavy role. C#, Docker, Kubernetes are your daily tools, not nice-to-haves. The AI layer sits on top of a solid backend foundation — and that foundation is yours to co-own.
Here's what you'd actually work on:
One example: a client sends a project brief. Instead of a creative director manually turning it into tasks and structure, an agent does the first pass, draft project setup, task breakdown, first feedback round, before the human team steps in. You'd build that.
A typical week looks like this: you analyse a customer workflow, build a first agent prototype with Nils and Sebastian, ship it to a test group, collect feedback, iterate. You're in product discussions, not just delivery. Minimal manual coding, maximum iteration — we work with Codex, Claude Code and Cursor daily. AI isn't in the job title, it's in every pull request.
👆Here's the job:
- Ship LLM-powered features end-to-end, from idea to real users
- Build and iterate on agents that work autonomously within project context
- Integrate LLMs via API (OpenAI, Anthropic): tool calling, streaming, RAG
- Co-own backend infrastructure: C#, Docker, Kubernetes
- Work closely with product: understand customer requirements, prioritise, build and ship to first users
- Treat prompts as code, write, test, evaluate and improve
- Proactively spot new opportunities where agents can create value
🧰 Technologies
- C# (.NET), Docker, Kubernetes, Agent Sandbox
- OpenAI / Anthropic API, multiple LLMs via API
- AI coding tools: Codex, Claude Code, Cursor
- TypeScript or React (nice to have for occasional frontend work)
🌟 Our wish list:
Must haves:
- You've shipped LLM features, as part of your role or a side project with real traction
- Solid backend experience: C#, Docker, Kubernetes
- You know how to integrate LLMs (tool calling, streaming, agents, RAG)
- You think in user journeys, not in models or endpoints
- Comfortable with ambiguity and fast iteration
- English C1
Nice to haves:
- First hands-on experience building agents, even at early-stage or prototype level
- Fullstack experience, with a clear backend focus
- Side projects with actual users
🚀 What makes you successful in this role:
- You take initiative and don't wait for the perfect brief
- You have a strong technical base and product thinking in equal measure
- You're pragmatic: done and learning beats perfect and waiting
🫶 Why awork?
- We make teams happy: our customers genuinely love the product, and that makes building it worth it.
- Real context, real value: awork has what most AI tools don't, actual project data. Time entries, team availability, task history, budgets. You build on top of that context to ship features that create real, measurable value for users. No synthetic demos, no hallucinated data.
- Real impact: features ship to 10,000+ teams. Not internal tooling.
- Doubling down on AI: you're joining a dedicated team we're forming specifically to accelerate AI development at awork. This is a serious investment, not a side project, and you'll help shape both the product and the team from early on.
- Adventurous culture: we try things before the hype arrives. "Be an adventurer" is a real value, not a poster.
- Hybrid setup: Hamburg office, open to other locations. We use Slack, Zoom, Gather and of course awork.
We’re a hybrid team, so we’re looking for someone comfortable with asynchronous communication and collaboration, but also excited to spend time with the team. We use tools like Slack, Zoom, Docs and of course, awork, to stay organized. We love coming together as a team—whether remote or in person. In our first chat, we’d be happy to tell you more about our team culture at awork.
Interested? 🤩 🚀
We can’t wait to receive your application! Let us know when you can start (spoiler alert: we’re in a hurry, as always).
Benefits
@ awork Nice!


4 Schritte im Hiring-Prozess 🚀




Kennlern-Call
Nice to meet you! Nach deiner Bewerbung findet zunächst ein 30-minütiges Gespräch statt, in dem wir uns gegenseitig kennenlernen und die Erwartungen an die Stelle abstimmen.


Rollenbezogenes Interview
Runde zwei! In diesen Schritt sind Teamlead und ggf. einige Teammitglieder involviert. Ihr sprecht über deinen Werdegang, deine Fähigkeiten und Ideen. Dabei schauen wir auch auf die Praxis-Aufgabe, die du bereits erledigt hast.


Meeting mit den Gründern
The final step! In diesem Schritt lernst du zwei unserer Gründer kennen und sprichst mit ihnen über unsere Werte, die Teamkultur, das Arbeitsumfeld und unsere Vision.


Erhalte ein Angebot
Yeah! Wir würden sehr gerne mit dir zusammenarbeiten (und hoffen, dass es dir genauso geht). Wir werden dir ein konkretes Angebot machen, das du natürlich ablehnen könntest, aber nicht solltest. 😉



