Are you looking to have an impact on the daily life of millions of entrepreneurs in France (and tomorrow in Europe)? Are you looking for a work environment that values trust, proactivity, and autonomy? Are our Engineering principles aligned with your vision? Then Pennylane is the right place for you!
We aim to become the most beloved financial Operating System of French SMEs and Accounting Firms (and soon, European ones). We help entrepreneurs rid themselves of time-consuming tasks related to accounting and finance while giving them access to the key financial information they need to make the best decisions for their business.
Pennylane is one of the fastest growing Fintechs in France (and soon in Europe!). In 5 years of existence, we've managed to:
Make ourselves known as a groundbreaking accounting and financial software for small businesses and their accountants
Raise a total of €400 million, including from Sequoia — the famous Silicon Valley fund that invested early in companies like Google, Facebook, Airbnb, Stripe and Paypal
Grow from 7 cofounders to 1,000 happy Pennylaners, and earn a place among the greatest companies to work for in France (and remotely), with a 4.6/5 rating on Glassdoor
Build an international environment with more than 25 nationalities and a strong remote-friendly culture, where 30% of employees already work from all parts of Europe
Earn the trust of thousands of customers and accounting firms, with outstanding ratings
Reach more than 1,000,000 small and medium-sized enterprises (SMEs) and over 6,000 accounting firms using Pennylane in France
Pennylane is becoming the financial OS of European SMEs and accounting firms. And a growing share of the work done inside our product will come from agents, not only from humans. Our AI strategy operates at three layers: verticalized AI embedded in the product (Copilot & Autopilot), an agent interface that makes Pennylane readable and actionable by AIs (tools, MCP), and the Pennylane orchestrator agent itself (Studio Assistant).
Models are commoditizing fast. What makes the difference is everything around them: the harness, the context, the tools, the guardrails. And the evaluation that proves it works on real accounting workflows. That is exactly what this role owns.
By joining us as an AI Engineer, you will have a pivotal role in large projects, bringing your software engineering and applied LLM / agentic systems expertise to help us meet our high delivery standards, at scale and with the level of trust our users require.
As an AI Engineer, you will be part of one of our ML & AI teams (25+ people, growing from 2 to 5 teams by the end of 2026), depending on your profile and our needs:
AI Capabilities & Infrastructure (CAPI) : the shared foundations every squad builds on: agent harness, agentic runtime & sandboxing, model gateway, tool registry & MCP, guardrails, observability, LLM FinOps, and reusable AI capabilities.
Agent Behaviour : making our agents behave correctly, safely and measurably: behaviour steering, domain tuning, evaluation methodology & harness, and later model fine-tuning.
Studio Assistant : the financial orchestrator agent for accountants and SMEs: understanding intent, picking tools, launching jobs, producing reports, asking for validation when needed.
Whichever team you join, the core of the job is the same:
You will build and harden agentic loops in production : LLM call orchestration, tool calling, streaming & events, error recovery, checkpointing and resumability. With security, permissions and cost in mind (agentic RBAC, audit trail, isolated execution, token and latency budgets).
You will own context & memory engineering: context construction, retrieval, compaction, short- and long-term memory, and the latency / cost trade-offs that come with them.
You will make Pennylane usable by agents, turning business capabilities into well-specified, documented, versioned and tested tools exposed internally and through MCP, and steering agent behaviour (system prompts and instructions, skills, planning and tool-selection strategies, guardrails, anti-prompt-injection).
You will treat evaluation as a first-class discipline: golden datasets, LLM-as-judge, human eval, regression tracking and error analysis. Turning production failures into systematic improvements.
You will collaborate with Product teams and domain experts (accountants) on live use cases : ComptAssistant, Studio Assistant, MCP, document extraction, Autopilot bookkeeping, revision. To make sure that fulfilling real user needs is always at the center of what we do.
Stay Ahead of the Curve: Continuously monitor the AI landscape for emerging trends, State-of-the-Art (SOTA) models, and breakthrough research (e.g., new LLM architectures, multimodal AI, and optimization techniques).
Within one month:
You will learn everything about our company, our teams, and our vision during the first onboarding week.
You will get familiar with our stack and AI tooling (agent harness, tool registry & MCP, evaluation and observability tooling, model gateway), and have delivered a few small projects which will give you a concrete taste of our tools & processes.
You will be given time to meet your future stakeholders, and gain a deep knowledge of our product and operations.
Within 3 months:
You will be fully in charge of items in our roadmap, defining and prioritizing your tasks autonomously, and will own an agentic use case end to end in production, together with its evaluation set and quality metrics.
You will be comfortable with our technical stack (Python, agentic frameworks & MCP, evaluation and observability tooling, Kubernetes & AWS).
You will contribute to larger cross-team projects.
Within 6 months:
You will proactively contribute to the team's roadmap.
You will work with engineers and data practitioners on improving our agent harness, our evaluation practices and our AI platform.
You will share your learnings and best practices within the team.
And beyond: the ML & AI teams will continue growing with the company
Which means:
Opportunities to recruit and mentor new team members,
Increased accountability in project leadership,
Responsibilities to design and implement new processes, tools and best practices to make sure that your team works even more efficiently.
You're the right candidate if you:
Have 5–8 years of experience and are very strong in Python
Hands-on experience building LLM and agentic systems at scale in production: prompting, tool use, context construction, RAG, and handling failure, state and reliability (not just calling a model API).
Treat evaluation as a first-class discipline: golden datasets, LLM-as-judge, human eval, A/B testing, and measuring agent quality, regressions and edge cases.
Have a good grasp of applied LLM / ML and AI infrastructure (model serving, vector databases, cost and latency).
Nice to have: model fine-tuning and post-training (SFT, DPO, RL), MCP, and familiarity with Ruby.
Have a balanced blend of technical, business and product skills, communicate well (including with non-technical domain experts), and are fluent in English (French is not mandatory).
A first interview with our Talent Acquisition Manager
A case study interview to discuss a topic closely related to one of our priorities (75 min)
A past-project interview to hear about your experience (60 min)
An interview with our Tech & Product leaders to discuss our company culture (60 min)
Wherever you are based, you'll get 25 vacation days paid by Pennylane
You'll have a competitive compensation package
You'll get company shares to enjoy a piece of the success story you're building with us
You'll have a budget to turn your home into a more comfortable workspace, as well as a monthly allowance to work from a coworking space whenever you feel like it
Through our partner Gymlib, you'll have access to 8,000 fitness spaces in Europe and more than 300 wellness activities
You'll have access to Busuu to perfect your English or your French
You'll get the latest Apple equipment
Depending on the team and the requirements of the position, you'll be able to work remotely from your country of residence, as long as it is in Europe and within a maximum time difference of two hours from the CET time zone
We regularly come together for company events such as Tech Days (which bring remote Pennylaners together every 2 months) and our annual company seminar
If you are based in France, you'll have a French contract following French regulation, on top of the additional perks: 6 to 12 RTT, 5 weeks of PTO, lunch credits (Swile), Alan Blue healthcare cover, and regular events in cities where Pennylaners are mostly present (Lyon, Bordeaux, Nantes…).
We're working on providing those last advantages to people based outside of France as well, though it can be more complex depending on the country.
Recruitment scam attempts are on the rise. We invite you to remain vigilant during your exchanges.
Applications through official channels only: apply exclusively through our job postings published on our official platforms (career site, official partner pages).
Always verify the sender's email address: our communications are sent from professional email addresses with the domains @pennylane.com or @pennylane-partners.com.
We will never ask you for payment or financial information (bank details, payment for an interview, equipment purchases, etc.) as part of the recruitment process. If such a request is made to you, it is fraudulent — please do not respond and report it to us immediately.
We fully embrace diversity, equity and inclusion, and we're committed to providing equal employment opportunity regardless of gender, sexual orientation, origin, disabilities, or any other traits that make you who you are.
Données personnelles
Pennylane traite vos données pour gérer votre candidature et évaluer votre adéquation au poste. Si votre candidature n’aboutit pas, vos données peuvent être conservées 2 ans à compter de notre dernier échange ou de la clôture du recrutement afin de constituer & gérer un vivier de candidats. Vous pouvez vous opposer à tout moment et demander la suppression de vos données en écrivant à : [email protected].
Notre data policy
Personal Data
Pennylane processes your data to manage your application and assess your suitability for the position. If your application is unsuccessful, your data may be retained for 2 years from our last exchange or the closing of the recruitment process, in order to build and manage a candidate pool. You may object at any time and request the deletion of your data by writing to [email protected]. Learn more
Personenbezogene Daten
Pennylane verarbeitet Ihre Daten, um Ihre Bewerbung zu bearbeiten und Ihre Eignung für die Stelle zu beurteilen. Sollte Ihre Bewerbung nicht erfolgreich sein, können Ihre Daten bis zu 2 Jahre ab unserem letzten Austausch oder dem Abschluss des Rekrutierungsverfahrens gespeichert werden, um einen Kandidatenpool aufzubauen und zu verwalten. Sie können jederzeit Widerspruch einlegen und die Löschung Ihrer Daten beantragen, indem Sie an [email protected] schreiben. Mehr erfahren
Datos personales
Pennylane trata sus datos para gestionar su candidatura y evaluar su idoneidad para el puesto. En caso de que su candidatura no sea seleccionada, sus datos podrán conservarse hasta 2 años a partir de nuestro último contacto o de la finalización del proceso de selección, con el fin de constituir y gestionar una reserva de candidatos. Puede oponerse en cualquier momento y solicitar la eliminación de sus datos escribiendo a [email protected]. Más información
