Join the right .env
We're young, fast, and building at the front edge of AI: the kind of systems most teams are still writing decks about. You'll ship to production in weeks, not quarters, own what you build end to end, and work beside a small senior crew that moves quickly because everyone here is genuinely good at what they do.
Solution Architect
We're looking for an architect who still builds. This isn't a role where you produce a diagram and hand it to a delivery team. You sit in the first client conversation, shape the solution, write the parts that set the pattern, and stay with it until it's in production. If your best work happens in a slide deck rather than a repository, this isn't the fit.
The job lives where the technical and the commercial meet. You'll translate a business problem into a system, an architecture into an estimate a client can approve, and a constraint into a tradeoff everyone actually understands. That means being credible in a room with a CTO and equally credible in a code review the same afternoon.
What will be your responsibilities?
You'll own the shape of a solution from the first call. That starts with discovery: understanding what the client's business actually needs, what their existing systems and data can support, and where the real risk sits. It ends with a proposed architecture, a delivery plan, and an estimate you're willing to stand behind. You'll write the proposals and the technical documentation, and you'll present both to the people paying for them.
Once delivery starts you stay in it: setting up the foundations, making the decisions that are expensive to reverse, reviewing the work as it lands, and unblocking the team when reality disagrees with the plan. You'll also be the technical counterpart the client escalates to when something is wrong, and the one who tells them honestly when a scope change means a date moves.
Across engagements you'll help raise the bar: establishing the patterns our teams reuse, pushing back on architecture that's fashionable but unwarranted, and mentoring engineers into the judgment this role runs on. You'll also help scope new work as it comes in, including deciding when we're not the right partner for it.
This position is made for you, if you:
- Have designed and delivered systems you personally stayed accountable for after launch, not just designed them.
- Still write and review code, and want to keep doing so.
- Can scope and estimate honestly, including saying a number a client won't like.
- Think in tradeoffs rather than best practices, and can explain a decision to a CTO and to a junior engineer in the same day.
- Have opinions about when NOT to use microservices, event sourcing, Kubernetes, or an LLM.
- Are comfortable being the technical face of an engagement, including in the difficult conversations.
- Write clearly: the architecture that survives is the one someone else can read six months later.
- Work well with legacy: most systems worth improving already exist and can't be stopped.
- Handle ambiguity as the default state of a new engagement, and know which questions collapse it fastest.
- Give and take direct feedback without it becoming personal.
Tech skills
- Deep experience across the stack, in TypeScript and Node, Python, or both, with real production scars.
- System design at scale: data modelling, service boundaries, consistency, caching, queues, and failure isolation.
- Cloud architecture on AWS or GCP: networking, IAM, cost modelling, and choosing managed over self-run.
- Data architecture across relational, document, and vector stores, plus the pipelines that feed them.
- Integration work: third-party APIs, legacy systems, event-driven patterns, and migrations that run live.
- Security and compliance instincts: auth, tenancy, data residency, and what GDPR or SOC 2 changes about a design.
- A working grasp of AI system architecture: agents, RAG, evaluation, and the cost and latency envelopes they impose.
- CI/CD, infrastructure as code, observability, and the operational reality of running what you designed.
- Estimation and delivery planning: breaking a system into phases that ship value before they ship completely.
Our projects and stack
Our work spans AI products, fintech, healthcare, logistics, and B2B SaaS, usually as the engineering partner a company brings in when the stakes are high and the timeline is short. Engagements range from a greenfield platform where you set every decision, to threading AI capability through a system that's been running for a decade, where the architecture problem is the integration and the data rather than the model.
The default stack is TypeScript end to end: Next.js and React on the front, Node.js on the back, with Python wherever the AI and data work lives. Postgres for state, vector stores for retrieval, the major model providers behind an abstraction we control. Infrastructure runs on AWS, GCP, and Vercel with CI/CD and observability from day one. We tailor per engagement rather than forcing a template, and we expect an architect to argue for the tailoring: new tooling has to earn its place in a system somebody will maintain for years.
Benefits that we offer
- Fully remote across Europe, with flexible hours built around a few shared core hours.
- 22 paid vacation days, plus an extra day for every year you spend with us.
- Private health insurance.
- A yearly learning budget for courses, books, and certifications, plus a conference of your choice, on us.
- Paid research time: exploring what the new models can do is work, not overtime.
- Top-tier hardware and a paid subscription to every AI tool worth having.
- Direct mentorship from senior engineers and founders who still write code.
- A referral bonus when you bring us someone great.
Our hiring process
Four steps, two to three weeks end to end, and a human answer at every one of them. You’ll know where you stand the whole way through.
Intro call
Thirty minutes with an engineer, not a recruiter. We walk you through what we actually build and who for, you tell us what you want your next two years to look like, and we both decide whether it's worth going further.
Technical deep-dive
Ninety minutes on real work. We pull apart a system you've shipped, then work through a problem shaped like the ones we take on. No whiteboard trivia, no algorithm quiz you'd never use again.
Meet the team
A conversation with the people you'd sit beside every day, plus the founders. You ask the uncomfortable questions about deadlines, on-call, and disagreement, and get honest answers before you commit to anything.
Offer
We move fast here: a decision within a few days of the last call, with the offer, the level, and the reasoning behind both laid out in writing. If it's a no, you get the actual reason.
Attach your CV as a PDF and tell us why you are a good fit. An engineer reads every one.