Software Engineer (Python) - AI Platform

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.

Revolut's AI department drives innovation, powering products through a central platform and building specialised AI-driven systems deployed worldwide. Our mission is to build a world-class automated foundation that empowers our scientists and engineers to solve tomorrow's challenges today.

We're looking for a Python Software Engineer to build the core infrastructure that powers our AI ecosystem — from large-scale data pipelines to Generative AI applications. You'll create modern, production-grade systems from the ground up, solving complex engineering challenges at a global scale.

Responsibilities

• 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

Requirements

• 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-Haves

• 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