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

Side projects or contributions to open‑source projects

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