Backend Engineer – GenAI Platform (Production-Scale)

United States Digital Space LLC; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Scale AI is seeking a Backend Engineer to design, build, and scale backend systems for enterprise GenAI products. You will focus on reliability, performance, and deployment across Scale's and customers' infrastructure.

You will develop core services and APIs to securely integrate AI models and enterprise data, while architecting distributed systems for large-scale data processing and orchestration. This role emphasizes observability, security, and cross-team collaboration.

Qualifications

• 4+ years of experience developing large-scale backend or infrastructure systems.
• Proficiency in Python or TypeScript with API/backend design experience.
• Cloud infrastructure experience (AWS and Azure preferred), including Kubernetes and Terraform.
• Experience with relational and NoSQL databases and data pipelines.
• Hands-on GenAI applications, model integration, or AI deployment experience.
• Strong observability, CI/CD, and security practices for enterprise environments.
• Ability to balance rapid iteration with production-grade quality.

Responsibilities

• Design, build, and scale backend systems powering enterprise GenAI products.
• Develop core services and APIs integrating AI models and data sources.
• Architect scalable distributed systems for data processing and orchestration of GenAI workloads.
• Optimize backend performance for latency, throughput, and cost across multi-cloud environments.
• Manage and evolve cloud infrastructure (AWS, Azure, GCP) with automation and security.

Skills

Distributed backends

Python

TypeScript

CI/CD

Collaborative mindset

Tools

FastAPI

Flask

Express

NestJS

Terraform

Kubernetes

Docker

PostgreSQL

DynamoDB

Job description

Scale AI is seeking a Backend Engineer to design, build, and scale backend systems for enterprise GenAI products. You will focus on reliability, performance, and deployment across Scale's and customers' infrastructure.

You will develop core services and APIs to securely integrate AI models and enterprise data, while architecting distributed systems for large-scale data processing and orchestration. This role emphasizes observability, security, and cross-team collaboration.