AI is transforming industries, but most companies struggle to turn AI pilots into production systems that deliver real business value.
That’s where we come in.
Spryfox is a specialized AI engineering firm that creates custom AI models and solutions - making AI practical, impactful, and real. Since 2020, our team has been building production-grade AI solutions for global enterprises across legal, healthcare, manufacturing, and insurance sectors. We don’t just consult; we roll up our sleeves, write code, and ship systems that solve actual business problems at scale.
Now, we’re looking for exceptional developers to join us. Developers who don’t just want to work on AI—but want to work with AI every day. Developers who thrive on customer impact, who can architect systems end-to-end, and who are excited to help shape the future of a growing company. If you’re tired of corporate restrictions, endless meetings, and projects that never ship—if you want real ownership, direct customer relationships, and the freedom to use cutting-edge technology—keep reading.
At Spryfox, you won’t just experiment with AI, you’ll build and ship real systems alongside some of the industry's best engineers, with the ownership, impact, and technical freedom to do the best work of your career.
We’re looking for a Senior Solutions Engineer who will take full ownership of customer projects from conception through deployment. You’ll be the trusted technical partner for our clients, independently managing engagements while building cutting-edge AI-powered applications that deliver measurable business impact.
This role combines deep technical execution with client relationship management. You'll architect and build production-grade software solutions—from web applications and data platforms to intelligent systems that integrate proprietary Spryfox models, orchestrate agentic workflows, and leverage LLMs—while helping our clients unlock new possibilities and growing long-term partnerships. You'll be writing code, deploying to the cloud, and sitting with customers to understand their challenges and craft solutions that work.
Unlike big corporations where AI access is often restricted, at Spryfox we actively encourage using the latest AI technologies in your daily work. We believe staying at the cutting edge isn’t just about what we build for clients; it’s about how we work. This approach dramatically boosts productivity and keeps our team at the forefront of AI innovation.
Customer Engagement & Project Leadership
Full-Stack AI Engineering & Deployment
Innovation & Growth
In addition to your CV we would like you to email us here, and add a short text answering these 3 questions.
Please keep your total responses under 400 words.
We are looking for a Senior Data Scientist who is strong on the fundamentals - properly strong, the kind that survives questioning. Plenty of people can point a model at a column, call fit, read off 94% accuracy and feel done. The work we care about starts at that 94%, with the question of what the number is hiding.
Our data is mostly tabular, sometimes text, occasionally time series or signal, now and then images. Whatever the modality, it tends to arrive messy, incomplete, biased in ways nobody warned you about, and smaller than you would like. The algorithm is rarely the hard part. The hard part is understanding the data well enough to know which question is even answerable, and being willing to say so when it isn't.
You would own projects end to end - framing the problem with the customer, doing the analysis properly, and standing in front of stakeholders to explain what you found and how much weight it can carry. There is one thing about how we work that matters more than any of this. When something is wrong for a customer, we feel it, and it doesn't let go until it is fixed. Their problem becomes our problem. We don't reach for the contract or the scope to explain why something isn't ours to solve. We want the customer to actually succeed. We are looking for someone wired the same way.
Several years of industrial ML and data science experience. Real projects, real constraints, real stakeholders.
Statistical depth you can defend under questioning, without reaching for a hand-wave. You understand uncertainty and how to quantify it. You know what a confidence interval does and does not tell you, and what a p-value actually is - and, more revealingly, what it is not. You can feel the difference between a correlation that means something and one that is an artefact. You know what a hypothesis test assumes, and what quietly breaks when those assumptions don't hold.
A meticulous, close to pedantic relationship with your own results. A number that looks too good makes you suspicious rather than pleased. You check before you believe, and you check hardest when the work is your own.
The reflex to interrogate data before modelling it - to plot it, ask how it was collected, and notice what is missing or wrong before drawing a single conclusion.
Solid Python and the usual ecosystem (scikit-learn, PyTorch or TensorFlow as the problem needs). Comfortable on cloud, AWS in our case.
The ability to carry a room - explaining technical reality to business stakeholders in a way that lands, and caring whether the customer succeeds rather than whether the ticket is closed.
For this role, we don't read CVs first. The last time we posted a role we mostly found out who can click apply the fastest, and we would rather find out how people think. So there is no email or application button here.
Instead we invite you into the Den - a short set of hands-on problems that show us how you reason about data and uncertainty. They won't eat your weekend. If you find them interesting, that is already a good sign. Clear them, and then you upload your CV, and it lands with people who are keen to read it.
If that sounds like your kind of front door, come and show us how you think.
