Lead AI Engineer (Remote)

We are looking for a Lead AI Engineer to own the technical direction of AI systems across Finom and lead the engineers who build them.

This is a leadership role from day one. You will set the technical and quality bar, lead a team of AI engineers, and stay hands-on in the code. You have done this before — we are not looking for someone stepping into technical leadership for the first time.

You will build AI services for Finom customers, and internal platform solutions that allow other teams to ship AI capabilities of their own. You take architecture responsibility for the services you and your team develop, along with the alignment that comes with it — translating between business intent and technical reality, and challenging product decisions when they are wrong.

This is not a research role. It is a hands-on engineering leadership role focused on production-grade AI capabilities that create clear value for customers and the business.

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. 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.

What You Will Be Doing

Lead a team of AI engineers — set direction, review designs, and grow their technical scope through review, pairing, and design guidance

Own the architecture for the services you and your team develop — and write down the decisions, tradeoffs, and rejected alternatives so they can be reviewed and challenged

Build and ship AI-powered customer and internal solutions using LLMs, RAG, tool calling, workflows, and agentic patterns

Own AI systems end to end — problem framing, implementation, evaluation, deployment, monitoring, and iteration

Develop scalable and reliable inference pipelines with strong attention to latency, cost, security, and observability

Set the evaluation and quality bar — offline evals, online signals, failure analysis, and continuous improvement loops that other teams adopt rather than renegotiate per project

Design AI systems with auditability, model governance, and EU AI Act obligations built in from the start rather than retrofitted

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 rather than isolated demos

Tell a product stakeholder when the thing they asked for is the wrong solution, and be persuasive about the right one

Negotiate scope and sequencing with domain teams that have their own roadmaps and no obligation to yours

Decide what to stop doing — deprecate, simplify, or kill approaches that the evidence no longer supports

Shape the roadmap rather than only execute tickets

Who You Are

A leader who earns authority through technical credibility rather than title

Still an engineer at heart — close enough to the code and the designs to have an opinion worth defending

Comfortable being accountable for outcomes you did not personally build

Someone who has held a technical position against pushback, revised it when the pushback was right, and can tell the difference

Direct with stakeholders and with your team — you surface problems early, including the ones that reflect badly on your own decisions

Decisive under ambiguity: you make the call on incomplete information and revisit it when better information arrives

Clear in writing — able to make a technical argument that a non-engineer can follow and act on

Product-minded and focused on real user outcomes, not just model outputs

Curious, low-ego, and biased toward action; motivated by what the team ships, not only by what you ship yourself

Must-Haves

Proven experience leading a team of engineers, formally or as a tech lead, with responsibility for what the team delivered

Track record of owning the technical direction of a system used by teams other than your own

Experience changing a product or business decision through technical argument rather than escalation

Experience working directly with non-technical stakeholders on commitments and tradeoffs, not through a manager as intermediary

Experience growing other engineers through review, mentoring, or design guidance

Strong ownership mindset and the 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 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 grasp of the fast-moving AI landscape, with the ability to turn relevant advances into practical product and engineering decisions

Fluent English (C1)

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

Tech Stack