Staff Applied AI Engineer
Pleo, the spend management company with over 40,000 customers, is hiring a Staff Applied AI Engineer as one of the first members of its Data & AI Products team. You will build and ship multiple AI-powered product features across agentic workflows, spend intelligence and automated actions, set the bar for AI delivery at Pleo, and own evaluation, monitoring and operationalisation of AI features at scale. The role requires deep applied AI judgment, staff-level autonomy and cross-functional influence. Remote, hybrid or in-person setups are possible in the listed locations, without visa sponsorship.
Responsibilities
- ▹Build and ship multiple AI-powered product features across agentic workflows, spend intelligence and automated actions, setting the delivery bar at Pleo
- ▹Bring deep applied AI expertise and 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 what is worth building, discovering and defining the product
- ▹Own evaluation, monitoring and operationalisation of AI features: setting up evals, tracking drift and performance, managing prompt changes safely in production
- ▹Act as a design partner to the GenAI Core platform team: challenge decisions with evidence, bring clear requirements, validate platform choices in production
- ▹Establish and enforce practical standards for AI feature delivery in product squads (evaluation strategy, monitoring, safe prompt/versioning practices, privacy and safety guardrails)
- ▹Upskill the team through mentorship, reviews, pairing and lightweight playbooks
Requirements
- ▹Proven experience shipping multiple GenAI features into production at scale in a customer-facing product, ideally including multi-step, tool-using agents
- ▹Ability to translate complex business challenges and product visions into scalable AI solutions: autonomously scope, design and build
- ▹Deep applied AI judgment about evaluation, retrieval quality, tool use, failure modes and what is worth building
- ▹Experience applying evaluation and observability to LLM systems (tests, golden sets, online metrics, monitoring) and iterating on those signals
- ▹Strong understanding of privacy and security concerns in LLM applications: prompt injection, PII handling, data leakage risk
- ▹Solid experience with the modern AI stack: vector databases, orchestration and durable execution frameworks, LLM APIs
- ▹Experience building APIs, services and data retrieval pipelines (RAG, vector search) to feed data into LLMs
- ▹Deep proficiency in Python for data and ML engineering, SQL and major cloud providers
- ▹Extensive background in traditional ML engineering and architecting reliable, scalable production data systems
- ▹Ability to influence cross-functionally with Product, Design and Engineering
Nice to have
- ▹Experience with Pleo's stack: GCP, BigQuery, Airflow, Python and SQL on the data side; AWS, Kotlin, JavaScript, TypeScript on the product side; Kubernetes-based infrastructure
Soft skills
What we offer
- ▹Your own Pleo card (no out-of-pocket spending)
- ▹Catered lunch or lunch allowance on work days, depending on the local office
- ▹Comprehensive private healthcare (Vitality, Alan or Médis depending on location)
- ▹25 days of holiday plus public holidays
- ▹Hybrid and fully remote working options
- ▹Free mental health and well-being support via MyndUp
- ▹Paid parental leave
About the company
Pleo builds spend management solutions that make handling company money seamless for finance teams and employees alike. Over its 10-year history it has grown to more than 40,000 customers, with a team of 850+ people from over 100 nationalities.