Staff Applied AI Engineer

This is an exciting opportunity to help shape how Pleo builds AI-powered product features, working alongside software engineers, data engineers and data scientists to take ideas from prototype to production. Pleo has over 40,000 customers and a decade of unique spend data — an incredible foundation to build on. Your mission will be to harness this data to create real product value. Your core focus is on building and shipping AI-powered features, with a strong collaborative element across Product Engineering, AI Platform, and Data & ML Platform teams.

Responsibilities

Build and ship multiple AI-powered product features, setting the bar for delivery at Pleo, across agentic workflows, spend intelligence, automated actions, and more; Bring deep applied AI expertise and strong judgment on trade-offs (quality vs latency/cost, build vs buy, agent patterns vs simpler approaches) and help teams avoid hype-driven decisions; Work directly with Product, Design, Engineering, and business stakeholders to advise and prioritise on what's actually worth building; Own the evaluation, monitoring, and operationalisation of AI features: setting up evals, tracking drift and performance, and managing prompt changes safely in production; Act as a design partner to the GenAI Core platform team: challenge decisions with evidence from real feature delivery, bring clear requirements, and validate platform choices in production; Establish and enforce practical standards for AI feature delivery in product squads (evaluation strategy, monitoring expectations, safe prompt/versioning practices, privacy & safety guardrails) using GenAI Platform tooling; Upskill the team through mentorship, reviews, pairing, and lightweight playbooks that make other engineers faster

Requirements

Proven experience shipping multiple GenAI features into production, at scale in a customer-facing product; You've moved past prototype phases; Ability to translate complex business challenges and product visions into scalable AI solutions; Deep applied AI judgment: ability to reason about evaluation, retrieval quality, tool use, failure modes, and what is/isn't worth building; Experience applying evaluation and observability to LLM systems (tests, golden sets, online metrics, monitoring) and using those signals to iterate; Strong understanding of privacy and security concerns when building LLM applications: prompt injection, handling PII and data leakage risk; Solid experience with the modern AI stack including Vector DBs, orchestration and durable execution frameworks, and LLM APIs; Experience building APIs, services and data retrieval pipelines (RAG, vector search etc) to feed data into LLMs; Deep proficiency with Python for both data and ML engineering, SQL and major cloud providers; Extensive background in traditional ML engineering and deep understanding of how to architect and build data systems for reliable and scalable production-use; Ability to influence cross-functionally with Product/Design/Engineering and bring teams along on decisions

Nice to have

Experience shipping multi-step, tool-using agents in a user-facing product; Experience with GCP, BigQuery, Airflow, AWS, Kotlin, JavaScript, TypeScript, Kubernetes

Benefits

Own Pleo card; 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; 25 days of holiday + public holidays; Hybrid and fully remote working options; MyndUp free mental health and well-being support; Paid parental leave