Senior AI Engineer

About the opportunity

About Finom Finom is a European tech startup headquartered in Amsterdam, and we’re on a journey towards revolutionizing the financial landscape for entrepreneurs worldwide. Our mission is to develop an all-in-one financial B2B solution that integrates banking functions, accounting, financial management, and invoicing into a seamless, mobile-first platform. We recently closed a €115 million Series C equity round (around $133 million), bringing our total funding to approximately $346 million. This significant investment follows a $105 million growth funding round from General Catalyst, a long-term backer since 2021 known for supporting companies like Airbnb, HubSpot, KAYAK, and Stripe. Finom's platform goes beyond traditional banking, offering invoicing and a growing suite of features, including AI-enabled accounting, aiming to simplify financial management for entrepreneurs. We're actively expanding our reach across key EU markets like Germany, France, the Netherlands, Italy, and Spain. At Finom, we’re not just redefining the entrepreneurial experience — we’re empowering our employees to make a real difference. Your work matters, and your impact extends far beyond product metrics. We nurture innovation and an inspiring work environment where bold ideas thrive, prioritizing thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and our business as a whole. Maintaining our start-up spirit, we prioritize thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and, of course, our business. We are looking for a Senior AI Engineer to design, build, and operate AI systems that solve real business problems across Finom. This role is for someone who can move comfortably from prototype to production: shaping the solution, building the system, measuring quality, and improving it over time. You will work on high-impact initiatives across onboarding, customer support, AI accounting, fraud and risk workflows, document understanding, internal automation, and agentic systems used by multiple teams. This is not a pure research role. It is a hands-on engineering role focused on delivering production-grade AI capabilities that create clear value for customers and the business. What You Will Be Doing Build and ship AI-powered product and internal solutions using LLMs, RAG, tool calling, workflows, and agentic patterns Own AI systems end-to-end: problem framing, architecture, implementation, evaluation, deployment, monitoring, and iteration Partner closely with solution managers, domain teams, and engineers to integrate AI into real workflows rather than isolated demos Design quality and evaluation frameworks for AI systems, including offline evals, online signals, failure analysis, and continuous improvement loops Develop scalable and reliable inference pipelines with strong attention to latency, cost, security, and observability Work on use cases such as onboarding, customer care, transaction and document classification, knowledge assistants, fraud detection, and operational automation Contribute to AI platform and tooling decisions that improve reuse, speed, and consistency across teams Challenge assumptions, propose better approaches, and help shape the roadmap rather than only execute tickets Experiment boldly, learn quickly from failures, and turn insights into stronger systems and better practices What Success Looks Like In your first 6 to 12 months, you will: Become fully embedded in the team and business domains you support Deliver at least one significant AI capability into production Generate visible impact through revenue uplift, cost savings, productivity gains, or risk reduction Raise the technical bar for how Finom builds, evaluates, and operates AI systems Help other teams adopt AI more effectively through strong engineering practice and pragmatic guidance Who You Are A strong software engineer with deep Python experience and a track record of shipping production systems Comfortable across the full lifecycle: prompting, retrieval, experimentation, evaluation, deployment, and production support Strong at turning ambiguous business problems into robust technical solutions Product-minded and focused on real user outcomes, not just model outputs Autonomous, pragmatic, and able to keep momentum without heavy supervision Clear in communication and comfortable working across functions Curious, proactive, low-ego, and biased toward action Someone who actively keeps up with the fast-moving AI landscape and can separate hype from what is actually useful Must-Haves Proven experience building and deploying AI systems in production Strong Python and software engineering fundamentals Hands-on experience with LLM applications, including some of: 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 ownership mindset and ability to work through ambiguity Actively experiments with new AI models, tools, and agentic patterns, and can evaluate which approaches are worth productionizing Strong grasp of the fast-moving AI landscape, with the ability to turn relevant advances into practical product and engineering decisions Fluent English Nice-to-Haves Experience in fintech, financial services, risk, compliance, or operations-heavy environments Experience with applied ML beyond LLMs, such as classification, anomaly detection, ranking, or document intelligence Experience with vector databases, knowledge systems, and retrieval infrastructure Experience with model benchmarking, experimentation frameworks, and cost or latency optimization at scale Background in startups or as a founder Contributions to open-source or visible side projects in AI Example Tech Stack You do not need experience with every item, but this role will likely involve technologies such as: Languages: Python, SQL, noSQL LLM / AI: OpenAI, Anthropic, LangGraph, Hugging Face, Ollama, PyTorch, OpenClaw Patterns: RAG, tool calling, agent workflows, eval pipelines Infrastructure: Docker, Kubernetes, AWS / GCP / Azure Data / Platform: Vector databases, event-driven systems, APIs, observability tooling What You Will Get In Return Make a genuine impact on the product Join our upward trajectory, and grow with us. We provide the resources and opportunities for continuous personal and professional development, empowering you to make a genuine impact on our evolving product. Work in the EU Embark on this exciting journey with us and enjoy the flexibility of traveling and working remotely or in a hybrid model across Europe. Become a stock options holder Unlock your inner entrepreneur and align your aspirations with ours through our Stock Options Program. This exciting opportunity is available to every team member, from junior team members to our founders. Receive unwavering support and care Finom stands by you at every step, embodying our commitment to your well-being and success reflected in our modern, friendly, and eco-conscious corporate culture. We offer constant support and care to ensure your Finom experience is successful and fulfilling. Work & Swim program Immerse yourself in our exclusive Work & Swim Program. Spend one month in a comfortable corporate apartment in enchanting Cyprus. It's the ideal opportunity to strike the perfect work-life balance while enjoying breathtaking Mediterranean views. Equal Opportunity Statement At Finom, we're an equal opportunity employer and value diversity at our company. We embrace diversity and invite applications from all walks of life. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, disability status, or other applicable legally protected characteristics.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.