Mid-Level Site Reliability Engineer - Remote AI/ML Cloud

SMX; Dover; Remote; GBP 72,000 - 120,000; Full time

Benefits offered by this job

Health insurance

Paid leave

Retirement

Job summary

SMX is seeking a Mid-Level Site Reliability Engineer to architect, automate, and operate high-performance cloud infrastructure for AI/ML platforms. In this role, you will bridge MLOps and DevSecOps, deploying scalable, cloud-based architectures that support compute-intensive AI workloads for enterprise and public-sector clients across commercial, private, hybrid, and government cloud environments.

Beyond hands-on platform engineering, you will serve as a customer-facing Technical SME, engaging

Qualifications

• 3 to 5 years of professional experience in SRE, DevOps, or Platform Engineering.
• Strong Kubernetes operations, container networking, RBAC and secrets handling.
• Experience across AWS / Azure / Google Cloud with IaC tooling and Git workflows.
• Automation in Python, Bash, or Go for platform automation.

Responsibilities

• Architect, deploy, and maintain highly available Kubernetes clusters for AI/ML workloads.
• Serve as technical SME on client engagements, shaping solutions and scoping work.
• Drive infrastructure automation with Terraform and GitOps from day one.
• Build CI/CD pipelines with vulnerability scans, artifact tracking, and audit trails.
• Monitor performance, capacity, and telemetry; participate in on-call rotations.
• Collaborate on network isolation, encryption, and key management across data pipelines.
• Produce runbooks, reference architectures, and client-ready documentation.

Skills

Kubernetes

Client & Consultation skills

CI/CD pipelines

Automation

Security & compliance

Cloud platforms

Troubleshooting

Observability

Tools

Terraform

GitOps

RBAC & Secrets Management

Job description

SMX is seeking a Mid-Level Site Reliability Engineer to architect, automate, and operate high-performance cloud infrastructure for AI/ML platforms. In this role, you will bridge MLOps and DevSecOps, deploying scalable, cloud-based architectures that support compute-intensive AI workloads for enterprise and public-sector clients across commercial, private, hybrid, and government cloud environments.

Beyond hands-on platform engineering, you will serve as a customer-facing Technical SME, engaging