DevOps Engineer

About the Role

We are building a next-generation cloud stack that combines containerised services with GPU-accelerated Windows rendering workloads running Unreal Engine. We’re looking for a DevOps Engineer who can design and implement a scalable AWS infrastructure that supports both Linux container services and an elastic Windows GPU “render/stream farm.”

You’ll be responsible for ensuring Windows GPU VMs in AWS (G5/G6 instance families) can be deployed, scaled, monitored, and integrated seamlessly into a wider cloud platform.

Key Responsibilities

Infrastructure Design & Automation

Design and implement AWS infrastructure for Linux-based services (EKS, ECS, RDS, S3, etc.) and GPU-enabled Windows VMs for Unreal Engine workloads.

Build automated pipelines (Terraform, CloudFormation, CDK) to deploy and scale GPU instances on demand.

• Windows GPU Scaling

Configure and manage AWS G5/G6 instance fleets or Auto Scaling Groups for Unreal Engine rendering and streaming.

Develop and optimise custom AMIs with Unreal Engine, NVIDIA drivers, and supporting software.

Implement cost-effective scaling strategies, including Spot instance utilisation for batch workloads.

• DevOps Tooling & CI/CD

Set up CI/CD pipelines (GitHub Actions/GitLab/Jenkins) for containerised services and Unreal Engine builds.

Manage artifact distribution (S3, ECR) and automate Unreal Engine deployment to GPU fleets.

• Networking & Security

Design secure VPC architectures connecting Linux EKS clusters and Windows GPU fleets.

Implement IAM, Secrets Manager, and least-privilege access controls.

Ensure GPU workloads can communicate privately with APIs, storage, and databases.

• Monitoring & Reliability

Deploy observability stack (CloudWatch, OpenTelemetry, or Prometheus/Grafana) for both Linux and Windows workloads.

Monitor GPU utilisation, frame render times, and cost per workload.

Define SLOs/SLAs for both container and GPU workloads.

• Required Skills & Experience

Proven experience as a DevOps / Cloud Infrastructure Engineer on AWS. Certification is a great to have.

Strong knowledge of AWS services: EC2 (G5/G6), Auto Scaling, EKS/ECS, RDS, S3, CloudWatch, VPC networking.

Experience with Windows Server on AWS and GPU driver/runtime management (NVIDIA GRID, CUDA).

Hands-on with Terraform (or CDK/CloudFormation) for reproducible infrastructure.

Familiarity with CI/CD pipelines for both Linux containers and Windows builds.

Strong skills in monitoring, logging, and scaling strategies.

Good grasp of cost optimisation in GPU-heavy environments (Spot vs On-Demand, autoscaling policies).

Nice to Have

Experience deploying Unreal Engine in the cloud (Pixel Streaming, render farms, batch rendering).

Familiarity with AWS queue systems.

Knowledge of containerised AI/ML pipelines (LangChain, vector databases, etc.).

Understanding of hybrid architectures (Linux + Windows + GPU workloads).