DevOps Engineer

DGH Recruitment; City Of London; On-site; GBP 85,000 - 115,000; Full time

Job summary

DGH Recruitment seeks an experienced MLOps Engineer to design and operate a secure, scalable AI platform on-site in London. You will collaborate with Data Science and Engineering teams to deploy robust infrastructure and reliable CI/CD pipelines.

The role focuses on building observable, cost-efficient platforms with IaC automation, ensuring security, high availability, and seamless AI workloads management.

Qualifications

• 5+ years' experience in Platform Engineering / DevOps.
• Strong experience with AWS and cloud-native architectures.
• Proven knowledge of 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.

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

MLOps

Platform engineering

CI/CD pipelines

DevOps best practices

Security & reliability

Python/Go/Node.js

Tools

AWS

Kubernetes

OpenTelemetry

Datadog

Job description

MLOps Engineer (Platform / DevOps) - AI Platform - FULL TIME ONSITE

We're partnering with a leading organisation on a high-profile AI initiative, seeking an experienced MLOps / Platform Engineer to build and scale infrastructure supporting advanced AI solutions.

The Role

You’ll play a key role in designing and operating a secure, scalable platform for deploying AI workloads and agents. Working closely with Data Science and Engineering teams, you’ll ensure robust infrastructure, seamless deployment pipelines, and high platform reliability.

Key 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

Key Requirements

• 5+ years' experience in Platform Engineering / DevOps
• Strong experience with AWS and cloud-native architectures
• Proven knowledge of 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

Desirable Skills

• Experience working on AI / ML platforms or deployments
• Exposure to large-scale distributed systems
• AWS certifications