AI Engineer, Pennylane
Core AI
+ Company shares
Financial operating system for European SMEs
Open for applications
Financial operating system for European SMEs
501-1000 employees
Open for applications
+ Company shares
501-1000 employees
Company mission
To build the leading financial tool for European SMEs.
Role
Who you are
- Have 5–8 years of experience and are very strong in Python, with 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)
- Have exposure to model fine-tuning and post-training (SFT, DPO, RL)
- 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)
- To speak English (levels are assessed and appreciated according to the department you're applying to)
- To be energized by an ever-shifting work environment
- To be highly collaborative (within your team and with other stakeholders)
- To be sufficiently experienced to prioritize business-led actions in your day-to-day activity
- We know that some people are less likely to apply than others if they don't feel like they meet the full list of criteria. If you're hesitating, we encourage you to apply: who knows, it might be the start of a meaningful and long-lasting collaboration
What the job involves
- The Core AI team sits at the heart of our AI strategy: while our solution squads (Copilot, Autopilot, AI Studio) build customer-facing AI features, Core AI builds the shared foundations they all rely on, giving Pennylane a durable technical edge — including on cost and sovereignty
- By joining Core AI as an AI Engineer, you'll play a pivotal role in large projects, bringing your engineering and machine learning expertise to build the agentic intelligence, quality and models that our solution squads rely on
- Build and maintain the agent harness — the core runtime that orchestrates LLM calls, tool use, context construction, memory and guardrails — and make it reliable in production
- Own the evaluation stack: design eval pipelines, golden datasets, LLM-as-judge and human-eval workflows; track agent performance, regressions and failure modes, and turn production failures into systematic improvements
- Do prompt and behaviour engineering and retrieval/RAG at scale, defining what "good" looks like for agents completing complex accounting workflows end to end
- Host and improve our own small models where it creates leverage: serving and inference of open-source LLMs, help fine-tuning and post-training (SFT / DPO / RL), and document-extraction models — for performance, cost and sovereignty
- Work closely with Product teams and domain experts (accountants) so that fulfilling real user needs stays at the center of what we build
- Within one month:
- You'll learn everything about our company, our teams and our vision during the first onboarding week
- You'll get familiar with our stack and AI tooling (agent harness, evaluation tooling, model providers, MCP), and deliver a few small contributions that give you a concrete taste of our tools and processes
- You'll be given time to meet your future stakeholders and gain a deep knowledge of our product and operations
- Within 3 months:
- You'll be in charge of items in our roadmap, defining and prioritizing your tasks autonomously
- You'll be comfortable with our technical stack (Python, agentic frameworks, evaluation tooling, model serving and AWS)
- You'll contribute to larger cross-team projects
- Within 6 months:
- You'll proactively contribute to the team's roadmap
- You'll work with engineers and data practitioners on improving our stack, AI platform and evaluation practices
- You'll share your learnings and best practices within the team
- And beyond — the team will keep 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 so your team works even more efficiently
- 💡Good to know: across our Tech organisation, engineers can take part in cross-cutting specialist groups ("fellowships") on topics such as evaluation, retrieval, prompt and behaviour design or model serving — a great way to share practices beyond your own squad
Application process
- 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)
Our take
In multiple mature markets, companies have been using QuickBooks, Xero and other SaaS solutions for accounting, but it is a fragmented industry with each country using its own software solution. In France, there is no definitive SaaS solution for accounting.
Pennylane wants to overhaul current tools and modernise the tech stack of accounting firms, by connecting directly with third-party services that hold valuable information. Accounting firms can use Pennylane collaboratively by accessing the platform to centralise receipts, create invoices and automate tasks. Instead of sending information back and forth with spreadsheets and photo attachments, both clients and accounting firms can interact directly on the platform.
Pennylane has a significant market opportunity ahead, with an ambitious goal to become the preferred management platform for European companies. The company already claims an impressive number of customers and strong backing which will allow it to further develop its platform and expand to other markets in Europe.
Freddie
Company Specialist at Welcome to the Jungle
Insights
25% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Jan 2026
$202.1m
SERIES E
Apr 2025
$86.6m
LATE VC
Total funding: $466.1m
Company benefits
- Work remotely from anywhere in Europe, as long as your contract allows you to
- Company shares to enjoy a piece of the success story you're building with us
- 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
- Access to 8000 fitness spaces in Europe and more than 300 activities related to wellness through our partner Gymlib
- Access to Busuu to perfect your english or your french
- The latest Apple equipment
- Be part of a vibrant social community: we do lots of sports together (running, climbing...), we love to hang out and have a drink together (Thursday afterwork drinks on our rooftop is a usual thing)
- Twice-a-year company seminars
- Wonderful office in the center of Paris
- 10 additional days off (to the 25 standard ones) for those based in France
- Lunch credits (Swile card) to buy your favorite food every day, for those based in France
- Great healthcare cover (Alan Blue) to take care of yourself and your family, for those based in France
Company HQ
Chaussée-d'Antin, Paris, France
Leadership
Arthur Waller
(Co-founder & CEO)Founded PriceMatch in 2012, and progressed from Product Owner to Senior Product Owner at Booking.com between 2015-2018. Co-founded Pennylane in 2020.
Felix Blossier
(Co-founder & COO)Founding Partner of PriceMatch in 2012 and experience as Director General of the French Treasury from 2018-2020. Co-founded Pennylane in 2020.
Tancrède Besnard
(Co-founder & CPO)Co-founded PriceMatch in 2012. Experience as Product Manager for Booking.com between 2016-2018, and current advisor for Predictus. Co-founded Pennylane in 2020.
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