Junior Site Reliability Engineer in Cardiff

Office requirements: Remote (central Cardiff office available 2 days a week)

This company provides managed AI operations for technology businesses. The service is not a traditional managed service model of cloud support and resets. The company operates, secures and governs the cloud, observability and AI runtime layer behind mission-critical software. The client's team owns the product, application, and model behaviour; we own the operating layer that keeps it reliable, secure, cost-controlled and evidence-ready.

Clients range from start-ups and scale-ups building fast without formal engineering controls, through to regulated, mission-critical platforms in fintech, healthtech and insurance, where the operating model and evidence trail matter as much as uptime. You'll work across traditional cloud platforms like Azure and AWS, as well as newer, AI-native application stacks such as Lovable, and the modern cloud platforms that often sit behind them, like Vercel and Supabase.

The company is a Datadog Advanced Partner (UK) and holds the accolade of being the world's first accredited MSP powered by Datadog. Datadog is a Nasdaq-listed observability platform. The company's technical focus is on observability and LLM observability specifically.

This is a chance to grow with a Cardiff business on the front line of AI-era cloud operations, with bleeding-edge tech, AI used responsibly, a team worth learning from, and the flexibility to do your best work. Other awards include the Sir Michael Moritz Tech Start-up Award.

• Runtime Assurance Delivery: Support customers across a mix of traditional and modern cloud platforms, Azure and AWS, alongside newer AI-native application stacks and the cloud platforms behind them, such as Lovable, Vercel and Supabase. Work through an ongoing ticket backlog per customer, sized to allow both reactive support and proactive improvement work. When a customer's backlog is empty, proactively review their environment for improvements rather than waiting for tickets to be raised.
• Observability & Datadog: Receive training on client environments and on the Datadog platform. Identify improvements independently, either by raising them to the team or by implementing them directly. Tickets may also be generated directly by Datadog alerts, covering both backlog items and live incidents.
• Build & Improvement Projects: Deliver end-to-end build-and-run projects for managed service customers, from scoping through to live operation. Implement cloud cost optimisation strategies, working through the technical dependencies that can sometimes block them. Manage monitoring and observability infrastructure as estates grow, keeping platforms performant and well-maintained. Build and deploy new infrastructure in Azure, including infrastructure-as-code, Datadog implementation, and APM setup, covering the full lifecycle from onboarding through go-live stabilisation.
• AWS Platform Work: Work hands-on with containers, EC2 and RDS instances across a range of customer environments, from day-to-day configuration and troubleshooting through to cost and performance optimisation. Also extends into AWS Bedrock for customers building AI-native products.
• Internal Tooling & Process: Contribute to a growing suite of internal AI tools built to improve engineering efficiency, reduce context-switching across platforms, and modernise how we run cloud operations day to day.

Review ticket queues across the managed service accounts. Project time is spent on a mix of Azure, AWS and Datadog implementation work, alongside newer platforms like Lovable, Vercel and Supabase. Work includes cost optimisation, infrastructure builds, and Datadog implementation and APM setup on live applications. On AWS, this includes container work, EC2 and RDS configuration, and Bedrock. Python is used throughout. Depending on the customer, this work may also involve GitHub Actions, Azure DevOps pipelines, or PowerShell scripting. Time is also allocated to internal work covering internal AI tools and process improvements. The role involves working across managed service delivery, project builds, observability, and internal tooling within the same week, rather than working on a single area on an ongoing basis.

• Working knowledge of at least one cloud platform (AWS or Azure)
• Comfort with scripting: Bash, Python, or similar
• Understanding of core observability concepts: metrics, logs, traces
• Clear written and verbal communication: you'll work with customers

• Hands-on Datadog experience (any tier)
• Terraform or other IaC tooling
• Kubernetes or containerised workload exposure
• Experience in a managed service provider or multi-customer environment
• Familiarity with ISO 27001 or similar compliance frameworks
• Any cloud certification (AWS, Azure, or Datadog)

Join a growing Cardiff business entering its scaling phase, with real ownership, visibility, and a chance to shape how a fast-moving modern MSP operates AI-era cloud infrastructure. On-call is documented, structured and remunerated in addition to salary. Training and tooling costs are paid for by the company. Attendance at industry events and courses is encouraged and funded as part of ongoing development. Employees are expected to identify and pursue improvements independently, without pre-defined limits on scope. Due to expected high demand, we'll be reviewing CVs as they come in and may close this role early once we've received sufficient applications.