Staff Software Engineer - Alwin

We are looking for a Staff Software Engineer in our Amsterdam office to build Alwin , our Agentic Automation Platform for audit and finance, and the systems around it. Alwin agents run multi-step audit procedures over client evidence and return finished workpapers with every number traced back to source. Humans plan, review and sign off. This is a hands-on role: most of your time will be spent writing code, building the hardest parts of the runtime, prototyping new capabilities and getting them into production. You lead by example: engineers follow your direction because they see it work in your code. Your impact will also come through the engineers and teams you work with. Your mission is to build the best agentic runtime for audit: one that completes audit tasks faster, more accurately, more reliably and at lower cost, while scaling to meet the needs of our largest customers. You will identify the problems that most constrain that mission, align teams around a technical direction and drive solutions through to measurable results, while building the foundations other engineers use and raising the quality of Alwin’s agents in production. Why DataSnipper? The hardest AI problems aren't about getting an answer fast. They're about getting one people can trust. We believe trust is essential to how society works. Every day, we rely on information that's been independently verified, from financial statements to the products we buy, to the sustainability claims companies make. Behind that trust are audit and finance professionals who examine evidence, verify information and hold organizations accountable. At DataSnipper, we build AI solutions that empower those professionals. By making evidence easier to trace and verify, we help them focus on the judgment and expertise that make their work so important. For our product and engineering team, this is where things get exciting. In audit, a plausible answer isn't good enough. Every output has to be explainable and traceable back to its source. We've just launched a brand new agentic platform, Alwin by DataSnipper. AI agents running in the cloud across hundreds of documents at once, reasoning across PDF, Word and Excel, with a full audit trail behind every step. There are lots of greenfield problems ahead, and real room to shape what we build and how we build it. And we build at scale. More than 600,000 professionals across 3,000+ organizations in 175 countries rely on DataSnipper, including Fortune 500 companies, government agencies and all Big Four audit firms. In 2025 alone, the DataSnipper platform delivered more than $1.4 billion in productivity savings to is customers . Backed by a $100 million Series B led by Index Ventures, at a $1 billion valuation, and as proud members of 1% for the Planet, we care about how we grow, not just how fast. If you want to build AI that professionals trust with work that really matters, this is your chance to help shape the future of audit and finance and do the best work of your career along the way.

What You Will Do

Results You Will Drive Better audit outcomes: improve how accurately and reliably agents complete real audit tasks, with traceable results and human oversight. A faster, more efficient runtime: reduce execution time and cost while scaling to more complex workloads and larger customers. More capable teams: build foundations and feedback loops that multiple teams use to ship and improve agents faster. Build & Ship Write production code every week on the most complex and critical parts of Alwin Build proofs of concept for new agent capabilities, and take the ones that work all the way to production Champion experimentation and R&D : try emerging models and techniques, solve hard problems creatively, and turn promising ideas into reliable features Build shared capabilities that multiple teams adopt , and remain accountable for whether they make those teams faster and their products more reliable Contribute directly to the agent harness at the core of Alwin: the orchestration, tools, context and evaluation loops every agent runs on Anticipate where the platform needs to be in 12 to 18 months, and make design decisions now that minimize the cost of future change Agents in Production Build agents that are reliable in a regulated domain : grounding, evaluation before release, human-in-the-loop, traceability of every action Improve how teams build Alwin by establishing tooling and feedback loops that help them detect agent failures, prioritize improvements, prevent regressions and ship production-ready agents faster Jump into the hardest incidents across teams , resolve immediate problems and turn what you learn into lasting, systemic fixes Make the trade-offs between model cost, latency and accuracy explicit, and measure them in production Lead by Example Own ambiguous, high-impact technical problems across teams : define the problem, align on the trade-offs and prove the solution in code Set the standard for code quality, testing and security through your own code and reviews, aligned with OWASP GenAI Drive AI-assisted engineering by example : try new tools, show what works and help teams adopt them Mentor senior engineers and grow future staff engineers by pairing, reviewing and building alongside them Work with Product to spot opportunities and differentiators against the competition, and shape the roadmap with what you have proven is possible What You Bring: 10+ years in software engineering, with strong, production-grade Python , and you still write a lot of code Deep hands-on experience building and shipping agentic or LLM systems in production yourself (control loops, tool calling, context engineering and evaluation), with evidence that your work improved quality, reliability, speed, cost or scale A track record of personally solving ambiguous, high-impact problems across teams . Your work delivered measurable results and produced systems or practices that others adopted Experience mentoring senio