Multi-Cloud Infra Engineer for Enterprise GenAI

Scale AI; York and North Yorkshire; On-site; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Health coverage

Wellbeing benefits

Career growth stipend

Parental support

Job summary

Scale AI is seeking a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. You will design multi-cloud solutions and implement integrations across cloud platforms to support diverse, regulated industries.

You will collaborate with platform, product teams and customers to develop scalable infrastructure, deliver high-velocity experiments, and contribute across the full product lifecycle while quickly learning new technologies.

Qualifications

• 4+ years of full-time engineering experience.
• Experience with large-scale distributed systems.
• Proficiency with Kubernetes, Python/JS/TS and SQL.
• Experience with major cloud providers (AWS, Azure, GCP).

Responsibilities

• Build and scale Scale AI’s core infrastructure in a fast-paced environment.
• Architect multi-cloud systems and abstractions for the SGP platform.
• Implement custom integrations between Scale AI’s platform and customer data environments.
• Collaborate with platform, product teams and customers to develop scalable infra.
• Deliver experiments at high velocity with quality to engage customers.
• Work across the full product lifecycle from concept to production.
• Be willing to multi-task and quickly learn new technologies.

Skills

Distributed systems

Kubernetes

Python/JavaScript/TypeScript

SQL

Cloud providers

Communication skills

Tools

Vector databases

Job description

Scale AI is seeking a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. You will design multi-cloud solutions and implement integrations across cloud platforms to support diverse, regulated industries.

You will collaborate with platform, product teams and customers to develop scalable infrastructure, deliver high-velocity experiments, and contribute across the full product lifecycle while quickly learning new technologies.