Senior Applied AI Engineer

Pleo
London, Lisbon, Copenhagen, Madrid
Workplace: HybridFull timeFunction: Data Science & Machine LearningSkills: ["Product instincts","Collaboration","Technical leadership","Communication","Problem-solving"]

Build and ship customer-facing AI features by designing end-to-end RAG systems, owning the full AI-product lifecycle from prompt/context and agentic workflows to safe production deployment. Create evaluation datasets and automated eval pipelines to measure quality pre/post changes, and instrument production observability (logging, drift detection, monitoring). Collaborate closely with Product Engineering, AI Platform, and Data/ML teams, and provide pragmatic technical leadership.

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FursaFursa
Pleo
Pleo
1 month ago

Senior Applied AI Engineer

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Build and ship customer-facing AI features by designing end-to-end RAG systems, owning the full AI-product lifecycle from prompt/context and agentic workflows to safe production deployment. Create evaluation datasets and automated eval pipelines to measure quality pre/post changes, and instrument production observability (logging, drift detection, monitoring). Collaborate closely with Product Engineering, AI Platform, and Data/ML teams, and provide pragmatic technical leadership.
Location: London, Lisbon, Copenhagen, Madrid
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build and ship AI-powered product features for customers, owning outcomes end-to-end within a scoped area.
  • •Design and implement end-to-end RAG systems, including chunking strategies, embedding model selection, retrieval optimization, and quality evaluation.
  • •Own the AI product lifecycle (prompt design, context/state management, agentic loops, output parsing, edge-case handling) and support safe production deployment.
  • •Create evaluation datasets and automated eval pipelines to validate AI feature quality before and after changes.
  • •Instrument AI features for production observability, including logging, drift detection, quality monitoring, and alerting.

Pay and Benefits

Perks:Health InsurancePaid ParentalMeal AllowancePaid Leave

Key Requirements

  • •Proven experience shipping customer-facing AI features using LLMs into real production with real users.
  • •Deep practical experience designing RAG systems and the full retrieval pipeline (embeddings, vector databases, chunking, hybrid search, re-ranking).
  • •Experience building and operating evaluation frameworks for LLM-based systems with a systematic quality-measurement approach.
  • •Strong Python engineering with production-grade, tested, maintainable code.
  • •Experience building APIs and data retrieval pipelines that feed context into AI systems.
Experience:SaaS
Skills:Product instinctsCollaborationTechnical leadershipCommunicationProblem-solving
Languages:English
Tech Stack:PythonLLMsRAGEmbedding modelsVector databasesChunkingHybrid searchRe-rankingPrompt designAgentic workflowsAWSGCPKotlinAPIDrift detectionLogging

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Pleo
Provides spend management software that helps businesses issue company cards, control expenses, automate reimbursements, and track team spending in one platform. Aims to simplify financial workflows for modern companies.
Industry: Fintech Infrastructure
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Headquarters: Copenhagen, Denmark
Founded: 2015
WebsiteLinkedIn