MLOps Platform Engineer - AI Infra & CI/CD

DGH Recruitment Limited; Greater London; On-site; GBP 90,000 - 110,000; Full time

Job summary

DGH Recruitment Limited is seeking an experienced MLOps / Platform Engineer to design, deploy, and scale AI infrastructure. You will work closely with Data Science and Engineering teams to ensure secure, reliable platforms for AI workloads and agents.

Based on-site three days per week, the role requires strong DevOps fluency, cloud, and automation skills, with a focus on performance, cost efficiency, and high availability.

Qualifications

• 5 years experience in Platform Engineering / DevOps.
• Strong AWS and cloud-native architectures knowledge.
• Experience with CI/CD, automation, and DevOps best practices.
• Experience with Kubernetes / containerisation technologies.
• Strong programming skills (e.g. Python, Go, Node.js).
• Experience with observability tools (e.g. OpenTelemetry, Datadog).
• Understanding of security, performance optimisation, and scalability.
• Experience with AI / ML platforms or deployments.
• Exposure to large-scale distributed systems.
• AWS certifications.

Responsibilities

• Design, deploy, and manage AI platforms and agent infrastructure
• Build and maintain CI/CD pipelines and DevOps workflows
• Implement observability, monitoring, and logging solutions
• Optimise performance, scalability, and cost efficiency
• Support AI teams with infrastructure, deployment, and integration
• Ensure platform security, compliance, and high availability
• Automate infrastructure using Infrastructure as Code (IaC) tools
• Troubleshoot and resolve platform issues

Skills

Platform Engineering

DevOps

AWS

CI/CD

Automation

Cloud-native architectures

OpenTelemetry

Datadog

AI/ML platforms

Distributed systems

Security

Performance optimisation

Kubernetes

Python

Go

Node.js

Tools

Kubernetes

Datadog

OpenTelemetry

Job description

DGH Recruitment Limited is seeking an experienced MLOps / Platform Engineer to design, deploy, and scale AI infrastructure. You will work closely with Data Science and Engineering teams to ensure secure, reliable platforms for AI workloads and agents.

Based on-site three days per week, the role requires strong DevOps fluency, cloud, and automation skills, with a focus on performance, cost efficiency, and high availability.