Salary: £80,000 – 100,000 per year
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 and containerisation technologies
- Strong programming skills, for example Python, Go, or Node.js
- Experience with observability tools, for example OpenTelemetry or Datadog
- Understanding of security, performance optimisation, and scalability
- Experience working on AI / ML platforms or deployments is desirable
- Exposure to large-scale distributed systems is desirable
- AWS certifications are desirable
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 tools
- Troubleshoot and resolve platform issues
Technologies
- AI
- AWS
- CI/CD
- Cloud
- Datadog
- DevOps
- Support
- Kubernetes
- OpenTelemetry
- Python
- Security
- NodeJS
More
We are partnering with a leading organisation on a high-profile AI initiative and are seeking an experienced MLOps / Platform Engineer to build and scale infrastructure supporting advanced AI solutions. This is a full-time onsite role where you will work closely with Data Science and Engineering teams to design and operate a secure, scalable platform for deploying AI workloads and agents. We offer the opportunity to contribute to a significant AI platform effort with strong focus on reliability, deployment pipelines, and infrastructure excellence.
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