Senior GenAI Platform Engineer

About Pleo

Messy spend management is tricky business. And tedious processes are a lose-lose situation for all involved, not just finance. At Pleo, we're changing that. We build spend solutions that make managing money seamless, empowering, and surprisingly effective for finance teams and employees alike - with a vision to help all businesses ‘go beyond’.

The word ‘Pleo’ actually means ‘more than you’d expect’, and living by that mantra has been the secret to our success over the last 10 years.

Now, we’re at a pivotal moment in our journey; every move we make has a direct impact on our 40,000+ customers, our business, and our collective success. We need people who take pride in uncovering customer needs, who turn complex problems into simple solutions, challenge the way things are done (respectfully), and always aim high. With great ambitions driving us forward, we can’t say we’ve got this whole thing figured out. And frankly, that’s half the fun! What we can say is that we’re a driven, progressive, and, importantly, a kind bunch of 850+ people from over 100 nationalities, all committed to delivering the future of business spending, together.

About the role

Pleo is investing heavily in AI-powered features across the product. You will be part of the GenAI Core team which is responsible for the horizontal platform infrastructure that makes this possible. They look afterLLM routing, MCP servers, vector search infrastructure, evaluation frameworks, and agentic tooling.

This is a hands-on backend/platform engineering role at the intersection of distributed systems and modern AI engineering. You will help design, build, and operate the shared AI infrastructure used by product teams across Pleo, with a strong focus on reliability, observability, security, and developer experience.

Who you’ll be working with and reporting to

You'll be reporting to the Engineering Manager for the GenAI Platform team and will be working closely with senior and staff Engineers in GenAI Core. You will also collaborate with Applied AI Engineers, Data Scientists, and product engineering teams across the business.

What you’ll be doing

As a Senior GenAI Platform Engineer you will:

• Design, build, and operate core GenAI platform components used by product teams at Pleo, including LLM routing gateway, vector search and RAG infrastructure, tool registry and MCP gateway, AI observability and evaluation tooling (tracing LLM calls, supporting human and automated evaluation, detecting drift, and tracking costs) and infrastructure for multi-step, long-running agentic workflows.
• Own production-quality delivery of platform features, from design through rollout, monitoring, and follow-up.
• Contribute to resilient system design: sensible APIs, failure handling, rate limiting, retries, idempotency, and safe change management.
• Improve reliability and observability through metrics, dashboards, alerting, incident follow-ups, and operational improvements.
• Partner with Applied AI Engineers and product teams to understand platform needs and help them build AI-powered features safely.
• Build internal SDKs, templates, and guardrails that let product engineers build AI features without needing deep infrastructure expertise.
• Support other engineers through pairing, code reviews, technical feedback, and clear documentation.
• Help evaluate build-vs-buy decisions in the rapidly evolving LLMOps tooling landscape.

What you bring

You will thrive in this role if you have:

• Strong backend/systems engineering background, with experience building and operating production services with reliability and observability requirements.
• Experience designing and delivering shared platform or infrastructure components used by multiple teams.
• Strong production ownership: monitoring, alerting, incident response, debugging, and post-incident learning.
• Distributed systems fundamentals, including async workflows, idempotency, consistency tradeoffs, and designing for failure.
• Hands-on experience with LLM APIs or strong interest in learning their production failure modes: rate limits, context windows, multi-vendor routing, latency variance, and cost control.
• Security mindset for AI systems, including prompt injection risks, PII in logs, data leakage, and safe credential handling.
• Strong programming experience in either a JVM-based language or Python. We operate a polyglot platform with components written in both Kotlin and Python, and you’ll be expected to contribute to both.
• Clear communication and collaboration skills, especially when working with product teams and other engineers to turn ambiguous platform needs into practical solutions.

Why is this role a good fit for you

This role is a good fit for you if:

• You are passionate about developer experience and get excited about being a force multiplier for engineering teams.
• You have moved past prototyping and have a deep understanding of the realities of LLMOps, data retrieval, prompt and context engineering, as well as model evaluation in production.
• You understand both the engineering and the data side of things, and are comfortable switching languages or technologies to achieve your goals.

This role is not a good fit for you if:

• You are primarily interested in model research or algorithm development. This role is about building the tooling that enables product teams to ship AI features to production.
• You prefer building customer-facing features. Your key users will be other Pleo Engineers.
• You cannot explain AI trade-offs clearly to non-technical stakeholders. You will regularly work with Product Managers, Designers, and business leaders who need to understand what is and isn't possible.

How you’ll develop in this role

In your first 6 months at Pleo, you’ll:

• Develop a clear picture of how AI features are currently being built at Pleo and where the biggest infrastructure bottlenecks are.
• Take ownership of a core platform component such as the LLM gateway, RAG infrastructure, MCP gateway, or evaluation framework, and improve its reliability, observability, or developer experience.
• Deliver production-ready improvements with clear rollout plans, monitoring, and operational documentation.
• Partner with Applied AI Engineers and product teams to identify platform investments that would accelerate their work.
• Contribute to Pleo's internal standards for AI feature development: how we evaluate quality, manage prompts, and monitor production AI systems.

We’re committed to helping you develop your career, whether that means taking on bigger projects, stepping into leadership, or acquiring new skills!

The location

Please note: We can hire on a remote, hybrid or in-person set-up in any of the locations listed on the advert but you will need to be physically based in the country of your choice with a valid right to work.

We are unable to offer visa sponsorship for this role.

Show me the benefits!

• Your own Pleo card (no more out-of-pocket spending!)
• Lunch is on us for your work days - enjoy catered meals or receive a lunch allowance based on your local office
• Comprehensive private healthcare - depending on your location, coverage options include Vitality, Alan or Médis
• We offer 25 days of holiday + your public holidays
• For our Team, we offer both hybrid and fully remote working options
• We use MyndUp to give our employees access to free mental health and well-being support with great success so far
• Paid parental leave - we want to make sure that we're supportive of families and help you feel that you don't have to compromise your family due to work

The interview process

We want to ensure you are set-up for success and understand what will be expected of you. If your application is successful, our interview process is as follows:

1. Intro call: A 30-minute chat with our Talent Partner to discuss the role and your background.
2. Technical screening: A 15 to 30 minute call with our Talent Partner to check your knowledge of key technical topics.
3. System design interview: A 75-minute practical session with our engineers focusing on scoping and designing an AI feature.
4. Live coding interview: A 75-minute practical session with our engineers focusing on implementing your solution.
5. Hiring Manager interview: A 60-minute conversation to deep dive into your knowledge and experience.
6. Final interview: A leadership interview focusing on your behavioural, communication and collaboration skills.

Transparency is important to us so we also wanted to share some insights about what we’re looking for in applications to ensure you can set yourself up for success!

• CV writing and content: we receive a lot of CVs, and many of them are AI-generated. We love seeing people leverage AI—it’s a big focus for us internally too—but without human intervention, these CVs can sometimes become generic and fail to show a candidate in the best light. What we're really looking for is the specific details of real impact that only you know from your previous experience. A top tip from us is to use the “Achieved X, as measured by Y, by doing Z” formula (credit: Laszlo Bock, ~2014) to give a really clear picture of what you’ve worked on. A final note: including links to your previous companies' websites is a huge help and allows us to truly understand your background!
• Application care: every single application we receive is reviewed by a human (yes, hundreds of them) because we believe that candidates' efforts should be matched by an equal level of human care. This means that we expect a similar level of attention put into your application. Read and answer the application questions carefully, they make a huge difference in our decision-making process.
• Profile to role fit: this is neither a research-driven nor a traditional data or software engineering role. We're looking for someone with proven experience building platforms or tooling for agentic AI. We expect senior-level engineers to be able to work fully autonomously on an entire product feature from design to implementation.

About your application

• English first. Since it's our company language, please submit your application in English. You’ll be using it a lot if you join us.
• A fair look for everyone. Our talent team reads every single application to ensure the process is fair. To keep things running smoothly, we only accept applications through our system—our support team can’t pass on calls or emails.
• Diversity drives us. We can only reach our goals if our team reflects the world around us. That starts with you hitting apply, even if you don't tick every single box. We encourage people from all backgrounds and experiences to join us.
• Interview at your best. We want you to feel comfortable throughout the process. If you have any accessibility requirements or need a specific format, email belonging@pleo.io. We’ll design a process that works for you.
• Your data is safe. When you apply, we process your personal data as a data processor. For more information on how Pleo processes personal data, read our Privacy Policy here.
• Applying for multiple roles? Nothing is stopping you, and we assess every role independently. However, we do look for alignment, so make sure you can explain why your interest and experience are right for each specific role.
• Reapplying. If you’re applying for the same role again, please wait six months from your last decision before hitting submit.