Remote Senior GenAI Platform Engineer in Wakefield

About Pleo

Messy spend management is tricky business. And tedious processes are a lose-lose situation for all involved, not just finance. 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’.

Pleo is investing heavily in AI-powered features across the product. They look after LLM 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.

You will also collaborate with Applied AI Engineers, Data Scientists, and product engineering teams across the business.

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.
• 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.
• Help evaluate build-vs-buy decisions in the rapidly evolving LLMOps tooling landscape.

Strong backend/systems engineering background, with experience building and operating production services with reliability and observability requirements.

Strong production ownership: monitoring, alerting, incident response, debugging, and post-incident learning.

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.

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 about building the tooling that enables product teams to ship AI features to production.

You prefer building customer-facing features. You cannot explain AI trade-offs clearly to non-technical stakeholders. Develop a clear picture of how AI features are currently being built at Pleo and where the biggest infrastructure bottlenecks are.

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!

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.

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.

A 30-minute chat with our Talent Partner to discuss the role and your background.

A 15 to 30 minute call with our Talent Partner to check your knowledge of key technical topics.

A 75-minute practical session with our engineers focusing on scoping and designing an AI feature.

Live coding interview: 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. A top tip from us is to use the “Achieved X, as measured by Y, by doing Z” formula.

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.

English first. Since it's our company language, please submit your application in English. Our talent team reads every single application to ensure the process is fair. Diversity drives us.

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