01
Intro call
Alignment on the role, expectations, and what you’re looking for.
Careers
Data & AI Graduate Engineer
A graduate role supporting data and AI delivery across AWS and Azure — with Datadog-based observability as a core skill from day one.
Datadog (essential)PythonAzure AIAWS BedrockObservabilityData pipelines
Location
Cardiff / London / Dublin (hybrid)
Employment
Full-time (graduate)
Level
Graduate / Early career
Team
Data & AI delivery (with Cloud Ops support)
Role overview
This role is designed for a graduate who wants to build practical skills across cloud, data, and AI — and who understands that production AI needs operational visibility, not just prototypes.
You’ll support delivery of data and AI projects on AWS and Azure (including Azure AI Services / Azure AI Foundry and AWS Bedrock), with a strong emphasis on monitoring and operational guardrails using Datadog.
You’ll learn how to ship safely: instrumentation, dashboards, performance signals, cost signals, and incident readiness for AI workloads.
What you’ll do
The day-to-day responsibilities of the role.
- Support delivery of data and AI projects across AWS and Azure environments.
- Instrument services and workloads so they’re observable in Datadog (metrics, logs, traces where relevant).
- Build dashboards that help teams understand reliability, latency, errors, and cost drivers.
- Help implement safe AI adoption patterns: auditability, human-in-the-loop checkpoints, and operational runbooks.
- Work with senior engineers to deliver POCs and pilots and move them toward production readiness.
- Write clean documentation and keep delivery artefacts organised and reproducible.
What you’ll bring
Datadog skills are essential for this role.
Must-have
- A degree (or equivalent experience) in a relevant discipline (CS, software, data, engineering, maths).
- Good Python fundamentals and the ability to learn new libraries quickly.
- Interest in cloud platforms (AWS and/or Azure) and modern data/AI services.
- Willingness to become hands-on with Datadog quickly (dashboards, monitors, signals).
- Clear written communication and a bias for asking good questions early.
Nice-to-have
- SQL fundamentals and basic data modelling understanding.
- Exposure to Azure AI Services / Azure AI Foundry or AWS Bedrock (even academic / personal projects).
- Basic understanding of observability (metrics vs logs vs traces) and why it matters in production.
- Experience with Git, CI/CD basics, or Infrastructure-as-Code concepts.
- Any Datadog coursework, labs, or certifications (not required).
What success looks like (first 90 days)
- You’ve built useful Datadog dashboards that reflect real operational questions (not vanity metrics).
- You can instrument a small service so key signals show up correctly in Datadog.
- You’ve contributed to at least one AI or data delivery milestone with clear documentation.
- You understand how we approach production readiness for AI workloads (cost, reliability, security).
How we hire
A simple process designed to respect your time.
02
Technical conversation
Real scenarios: Datadog signals, incidents, systems, trade-offs.
03
Practical exercise
A realistic task. No long take-home marathons.
04
Meet the team
Working style fit, then we move quickly.
Equal opportunities
Critical Cloud is an equal opportunity employer. We value diverse perspectives and are committed to creating an inclusive environment for everyone.
Apply for this role
Email us your CV and a short note on why this role fits you. We’ll get back to you as soon as we can.