Edge-Driven DevOps Engineer, AWS & Kubernetes

Atarus; England; On-site; GBP 70,000 - 110,000; Full time

Job summary

Atarus is partnered with a fast-growing AI company recruiting a DevOps / Infrastructure Engineer. You’ll build production-grade software for internal infrastructure, scale AWS and Kubernetes environments and develop edge-device provisioning and remote management systems.

The role emphasizes shipping software as well as infrastructure, with a strong ownership mindset. You’ll work in a small, highly technical team on real-world AI systems at scale, contributing to reliability, security and

Qualifications

• Strong Python or Go engineering skills.
• Production experience with AWS & Kubernetes.
• Experience building CI/CD, automation and observability systems.
• Edge / IoT experience is a bonus, not essential.
• Much more engineering-heavy than a traditional DevOps role.
• Real-world AI systems operating at significant scale.
• Small engineering team with high ownership and architectural influence.
• Strong commercial traction, significant backing and meaningful equity.

Responsibilities

• Build production-grade software for their internal infrastructure platform.
• Scale and evolve AWS & Kubernetes environments.
• Build provisioning and remote management systems for large fleets of edge devices.
• Develop CI/CD, deployment and automation tooling.
• Build observability and telemetry across cloud and edge infrastructure.
• Improve reliability, security and developer experience as the platform scales.

Skills

Python

Go

CI/CD

Automation

Observability

Edge/IoT experience

Tools

AWS

Kubernetes

IoT

Job description

Atarus is partnered with a fast-growing AI company recruiting a DevOps / Infrastructure Engineer. You’ll build production-grade software for internal infrastructure, scale AWS and Kubernetes environments and develop edge-device provisioning and remote management systems.

The role emphasizes shipping software as well as infrastructure, with a strong ownership mindset. You’ll work in a small, highly technical team on real-world AI systems at scale, contributing to reliability, security and