ai engineer in fintech

Finom is a European tech startup headquartered in Amsterdam that develops an all-in-one financial B2B solution for entrepreneurs, integrating banking functions, accounting, financial management, invoicing, and AI-enabled accounting into a mobile-first platform.

• Lead a team of AI engineers by setting direction, reviewing designs, and expanding their technical scope through review, pairing, and design guidance;
• Own the architecture of team services and document decisions, tradeoffs, and rejected alternatives;
• Build and ship AI-powered customer and internal solutions using LLMs, RAG, tool calling, workflows, and agentic patterns;
• Own AI systems end to end, including problem framing, implementation, evaluation, deployment, monitoring, and iteration;
• Develop scalable and reliable inference pipelines with attention to latency, cost, security, and observability;
• Set evaluation and quality standards through offline evaluations, online signals, failure analysis, and continuous improvement loops;
• Design AI systems with auditability, model governance, and EU AI Act obligations built in;
• Drive AI platform and tooling decisions that improve reuse, speed, and consistency across teams;
• Partner with solution managers, domain teams, and engineers to integrate AI into real workflows;
• Challenge product decisions and persuade stakeholders when another solution is more appropriate;
• Negotiate scope and sequencing with domain teams;
• Decide what to deprecate, simplify, or discontinue based on evidence;
• Shape the roadmap rather than only execute tickets.

• Proven experience leading an engineering team formally or as a tech lead, with responsibility for team delivery;
• Experience owning the technical direction of a system used by teams beyond your own;
• Experience changing product or business decisions through technical argument;
• Experience working directly with non-technical stakeholders on commitments and tradeoffs;
• Experience developing engineers through review, mentoring, or design guidance;
• Strong ownership mindset and ability to create clarity in genuine ambiguity;
• Proven experience building and deploying AI systems in production;
• Strong Python and software engineering fundamentals;
• Hands-on experience with LLM applications, including RAG, tool use, agents, prompt engineering, evals, structured outputs, guardrails, or fine-tuning;
• Experience integrating AI systems into backend or product workflows;
• Ability to design meaningful evaluation, monitoring, and continuous improvement loops;
• Experience with cloud infrastructure and containerized deployments;
• Strong understanding of the fast-moving AI landscape and ability to apply relevant advances to product and engineering decisions;
• Fluent English (C1);
• Nice to have: experience in fintech, financial services, risk, compliance, or operations-heavy environments, applied ML beyond LLMs, vector databases and retrieval infrastructure, model benchmarking and experimentation frameworks, cost or latency optimization at scale, startup or founder background, open-source contributions or visible AI side projects.

• Work across the EU with the flexibility to travel and work remotely or in a hybrid model across Europe;
• Stock Options Program available to every team member;
• Resources and opportunities for continuous personal and professional development;
• Work & Swim Program with one month in a corporate apartment in Cyprus;
• Modern, friendly, and eco-conscious corporate culture with ongoing support and care.