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 The GenAI Platform is Pleo's internal AI infrastructure team, the platform every customer-facing AI feature is built on.
The team owns LLM serving (LiteLLM), the MCP gateway and tool registry, agentic runtime, evaluation tooling, and the observability layer that makes AI outputs trustworthy at scale. This is a technical engineering management role for a builder-leader. You will lead a team of strong staff and senior engineers through a critical transition: evolving from a Kotlin-first SDK to a hybrid architecture that makes Python a first-class citizen for agentic development. You will own delivery of the platform roadmap, contribute to key technical decisions, and stay close enough to the work to shape architecture, unblock delivery, and set a high technical bar. This is a role for someone who can actively build the conditions, systems, and technical direction that help
the team ship. Who you’ll be working with and reporting to You will report to the VP of Data and work closely with Product, broader Engineering leadership, Data, Security, Risk and Legal teams. What you’ll be doing As an Engineering Manager, you will: Lead the GenAI Platform team day-to-day as a builder-leader: delivery, quality, team development, and ways of working. Own the execution of the platform roadmap including but not limited to LLM gateway, agentic runtime, MCP layer, data retrieval, eval tooling, and the hybrid architecture transition. Manage the stakeholders relationship with Data & AI Products as the primary internal customer and ensure the platform roadmap is shaped by product demand, not platform preference. Drive active hiring for
the team to build a team to deliver on the planned technical vision and roadmap. Partner with SRE on reliability standards, incident management, and production readiness for platform services. Represent
the team in leadership and cross-functional discussions ensuring to translate platform progress and blockers into terms that drive decisions. Own
the team's cost and resourcing decisions: LLM spend, infrastructure costs, headcount. For more context, our tech stack currently includes AWS, Kotlin, Python, Kubernetes. LiteLLM, BrainTrust, Temporal, LLM APIs and more. You do not need to be an expert across all of these, but need enough familiarity to follow technical discussions and make good trade-off decisions. What you bring You’ll thrive in this role if you have: Significant engineering management experience in platform or infrastructure teams, with demonstrated experience balancing technical delivery, hands-on technical judgment, and people leadership. Deep technical expertise in AI infrastructure enabling you to advocate for the users, make relevant technical decisions and actively take part in architectural discussion or hands-on work alongside team members. Experience managing senior, highly autonomous engineers. Demonstrated experience leading engineering teams through significant change. This team is in an architectural inflection point and you will need to maintain delivery velocity through this transition. AI-assisted engineering experience and familiarity delivering and driving outputs leveraging tools such as Claude Code (it is our tool of choice), Codex or Cursor. Why is this role a good fit for you This role is a good fit for you if: Your platform engineering understanding is as strong as your understanding of the data space. You will need to operate at the intersection of both worlds to be successful in this role. You keep up to date with technology changes and still get excited about doing hands-on work. You probably have been developing your own agentic solutions and are eager to make these available to a larger customer base. This role is not a good fit for you if: You are a pure people manager or coordination-only leader.
The team is building complex AI infrastructure and the manager needs to engage meaningfully with technical decisions, trade-offs, and delivery details. You do not have a deep knowledge of data/ML-heavy ecosystems. How you’ll develop in this role In your first 6 months at Pleo, you’ll: Develop a thorough understanding of the platform's current architecture, the hybrid architecture transition in flight, and the most significant gaps, identify and make significant improvements with
the team to achieve Pleo’s agentic goals. Establish a strong working relationship with
the team; understand how they work, what they need, and where the management gaps are. Own the platform roadmap and establish a clear delivery cadence. Progress the hiring plan. Define and land the stakeholders model: supporting
the team, how the platform roadmap is prioritised, how requests are handled, and what the support SLA looks like. 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 in any of the listed locations. 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 25-28 days of holiday (depending on your location) + public holidays 🏠 For our Team, we offer both hybrid and fully remote working options 🏖️ Option to purchase 5 additional days of holiday through a salary sacrifice ❤️🩹 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: Intro call: A 30-minute chat with our Talent Partner to discuss
the role and your background. Hiring Manager interview: A 60-minute conversation with our VP of Data, deep diving into your management experience, data & AI literacy, and product acumen. Technical interview: A 75 to 90-minute practical interview where we'll assess your knowledge of AI and product engineering on a real-life like scenario. Final interview: A 30-minute conversation with our Chief Product & Technology Officer to discuss strategic vision, values and business acumen. 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! We tend to receive really high volumes of applications for AI-related roles but less than 1% tend to be selected for an intro call. Some of the key reasons why previous candidates didn’t make it past the application screening stage include: 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: we are looking for extensive experience of building AI/data related products and concurrently managing multiple teams. If you have not worked in mature data and product engineering environments with a very deep understanding of both worlds, this role is not right for you. 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 [email protected]. 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.
