AI Solution Engineer

Role overview A full-time, remote engineering role based in Europe that sits at the seam between an AI platform and the financial services clients who use it. The work centers on turning messy, real-world financial workflows into dependable AI solutions that run in audited production environments. It is a high-ownership position spanning problem framing, solution design, hands-on building, and client-facing iteration.

Responsibilities - Translate client requirements into concrete AI workflows and ship end-to-end solutions on a node-based platform. - Compose agentic and multi-step workflows, including tool calling, retrieval-augmented generation, and prompting strategies that favor deterministic, schema-validated outputs. - Build solutions that handle challenging financial documents such as PDFs, spreadsheets, and email threads, including imperfect and edge-case data. - Work directly with client teams to validate outputs, gather feedback quickly, and harden solutions until they are accurate, auditable, and production-ready. - Own delivery from the first prototype through to a live deployment in a regulated system.

Requirements - Strong computer science fundamentals and curiosity about AI systems beyond surface-level usage. - Comfort with open-ended problem solving and clear written and verbal communication. - Willingness to learn independently and ask good questions when facing ambiguity. - Advanced English, both written and spoken.

Nice to have - Professional experience in backend systems, APIs, or machine learning tooling. - Hands-on work with LLM orchestration, retrieval pipelines, or other applied AI workflows. - Confidence working directly with stakeholders and translating fuzzy requirements into working solutions. - Genuine interest in system design and the constraints of real production environments.

Benefits and work setup - Full-time, fully remote within Europe. - Flexible start date, ideally as soon as practical. - Competitive salary plus meaningful early-stage equity. - Culture oriented around autonomy, focus, and ownership rather than hours logged. - Quarterly team retreats and exposure to real production AI deployments with real clients.