Software Engineer (Python) - AI Platform

People deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products — including spending, saving, investing, exchanging, travelling, and more — help our 70+ million customers get more from their money every day.

As we continue our lightning-fast growth,‌ 2 things are essential to our success: our people and our culture. In recognition of our outstanding employee experience, we've been certified as a Great Place to Work™. So far, we have 13,000+ people working around the world, from our offices and remotely, to help us achieve our mission. And we're looking for more brilliant people. People who love building great products, redefining success, and turning the complexity of a chaotic world into the simplicity of a beautiful solution.

• A degree in a STEM field or equivalent
• A solid foundation in computer science principles
• A proven track record designing and operating scalable backend systems in production environments
• Proficiency in Python as your primary language, with solid command of additional programming languages
• Expertise in distributed systems and modern infrastructure practices, like containerisation and orchestration
• Hands-on experience addressing challenges across the AI/ML lifecycle, including deployment, orchestration, and model management

Nice to have:

• Experience with infrastructure as code (IaC) tools, like Terraform or Ansible
• Familiarity with frameworks for high-performance model serving, especially for large-scale or Generative AI models
• Experience building internal platforms or developer tools
• Experience integrating third-party APIs and services to build resilient, production-grade solutions
• Knowledge of data and model versioning strategies and tools
• Side projects or contributions to open-source projects

• Designing, building, and maintaining scalable services that support the AI lifecycle
• Developing infrastructure and APIs that integrate third-party services and grow with the business
• Implementing and managing robust CI/CD pipelines to validate, deploy, and monitor a diverse range of models
• Building and scaling APIs and SDKs for serving AI models and systems
• Ensuring low latency and high availability to meet business needs
• Partnering with product teams to design and deliver accessible AI solutions
• Building frameworks to track data drift, model decay, and operational health
• Establishing the backbone for AI governance and reproducibility
• Versioning data and models and managing a central feature store
• Tracking lineage to ensure a clear, auditable path from research to production