Python platform engineer for AI agents

Our Technology team builds the systems and experiences that keep Revolut moving. From the infrastructure behind our innovative app to the features used by millions of people around the world, they bring sharp thinking, speed, and a focus on meaningful impact to everything they do. We’re looking for a Senior Platform Engineer (Python) with impressive backend engineering skills and hands-on experience building LLM agents. You’ll build the services, infrastructure, and tooling that enable teams across Revolut to develop, deploy, and operate reliable AI agents in a heavily regulated financial environment.

• Designing, building, and maintaining scalable Python services, APIs, and data pipelines for our internal agent platform
• Developing and deploying LLM agents, including tool integrations, orchestration, and state management
• Building reusable platform capabilities that help teams develop, test, and operate AI agents in production
• Improving agent reliability, observability, performance, and cost efficiency through evaluation, monitoring, and robust error handling
• Breaking down complex AI and backend engineering problems into technical designs, reviewable components, and executable delivery plans
• Reviewing designs and code, ensuring solutions are secure, maintainable, and suited to business needs

• 5+ years of experience as a software engineer, focusing on backend systems
• 3+ years of experience engineering with Python as your primary language
• Hands-on expertise developing LLM agents, with production experience in AI agent systems or platforms
• An academic background in STEM
• Fluency in SQL and proficiency in another object-oriented programming language
• Experience with API development, integration, and distributed systems
• The ability to write concurrent code for I/O-bound and CPU-bound workloads
• Familiarity with Docker, Kubernetes, CI/CD, monitoring, and alerting
• An understanding of production agent challenges, including tool execution, context management, evaluation, and failure handling
• The ability to translate ambiguous requirements into clear designs, explain technical trade-offs, and deliver work through well-defined implementation steps

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