Backend Engineer – GenAI Platform at Enterprise Scale

Scale; Greater London; On-site; GBP 75,000 - 110,000; Full time

Job summary

Scale is hiring a Backend Engineer to help bring large-scale GenAI systems to production. You will design scalable APIs, distributed data systems, and robust deployment pipelines that power enterprise AI products and services.

This role emphasizes reliability, performance, and production-grade quality across hybrid and multi-cloud environments, with close collaboration with ML, infra, and product teams to deliver end-to-end solutions for leading enterprises.

Qualifications

• 4+ years of experience building large-scale backend or infrastructure systems.
• Proficiency in Python or TypeScript and high-performance API design.
• Experience with cloud infra, containers, and IaC tools.
• Hands-on GenAI applications, data systems, and security practices.
• Strong CI/CD, observability, and production reliability mindset.

Responsibilities

• Design, build, and scale backend systems for enterprise GenAI products.
• Develop core services and APIs that securely integrate AI models and data sources.
• Architect distributed systems for data processing and orchestration of GenAI workloads.
• Optimize backend performance for latency, throughput, and hybrid/multi-cloud deployment.
• Manage cloud infrastructure (AWS/Azure/GCP) with automation and security.
• Collaborate with ML, infra, and product teams to productionize GenAI models.
• Improve reliability and scalability with robust engineering practices.

Skills

4+ years experience

Python or TypeScript

Cloud infrastructure

Observability/CI-CD

Collaboration

Tools

FastAPI

Flask

Express/NestJS

Kubernetes

Docker

Terraform

PostgreSQL

DynamoDB

Job description

Scale is hiring a Backend Engineer to help bring large-scale GenAI systems to production. You will design scalable APIs, distributed data systems, and robust deployment pipelines that power enterprise AI products and services.

This role emphasizes reliability, performance, and production-grade quality across hybrid and multi-cloud environments, with close collaboration with ML, infra, and product teams to deliver end-to-end solutions for leading enterprises.