Principal Cloud Engineer (Azure)

What you'll do

Set cloud strategy and architecture 

• Form and execute the cloud technical strategy with the Director of Cloud & Developer Operations, who retains accountability for organisational priorities, budget, people, reliability outcomes, and the operating model.

• Define reference architectures, standards, and reusable patterns; guide architectural decisions and hold coherent technical direction across teams, in partnership with the Chief Architect.

• Apply Cloud Adoption Framework (CAF) and Well-Architected Framework (WAF) thinking; design for scalability, including the SQL data estate beneath the platform.

Drive transformation 

• Take end-to-end technical ownership of infrastructure transformation projects — cloud modernisation, efficiency, and FinOps initiatives.

• Drive strategic cloud initiatives and major transformation efforts, and push the boundaries of scale, resilience, and efficiency.

• Bring AI-native operations into the lane — agents, bounded automation, and evals, with observability, approvals, containment, and rollback — so reliability and efficiency scale faster than headcount.

Lead and mentor 

• Mentor engineers on architecture, best practices, and complex problem-solving.

• Lead critical technical discussions and champion innovation; strengthen cross-team collaboration.

• Define and publish standards — make implicit expectations explicit and inspectable.

Partner and operate 

• Partner with business stakeholders so cloud solutions directly support TOPdesk’s strategic objectives.

• Refine operational processes so we stay both agile and highly reliable, and support 24/7 continuity of service (including a shared stand-by rotation).

• Identify dependencies early and cooperate with other engineering and non-cloud teams toward shared goals.

Technical environment

Claude Code is our current primary agentic engineering environment: agents may plan and execute within defined constraints and governed environments, while engineers stay accountable for problem framing, architecture, acceptance criteria, security, verification, and production outcomes. Agent-generated work is backed by automated tests, runtime checks, reviewable evidence, and risk-based human approval — we match deterministic automation, structured workflows, or agents to the nature and risk of the task rather than maximising autonomy for its own sake.

• Cloud: Microsoft Azure (networking, compute, storage) at multi-tenant SaaS scale; Kubernetes / Azure AKS.

• Infrastructure as code: Terraform via CI/CD; configuration management with Puppet and Ansible.

• Observability: metrics and monitoring stacks (e.g. Influx, VictoriaMetrics, Grafana, Nagios).

• Automation: Python and automation tooling — and we expect you to take the stack to the next level, not just operate today’s.

• Legacy: Java, MS SQL, heritage architecture — being decomposed.

• Mechanisms: subagents, MCP tool integrations, multi-agent workflows, and shared prompt, agent, and eval libraries.

Success in your first year

• A major infrastructure transformation is under your technical ownership and delivering — measurably better scale, resilience, or efficiency against a documented baseline.

• Architectural direction for the cloud platform is coherent across teams, with published standards engineers build on.

• Engineers you mentor are visibly stronger; you are consulted during design, not only after incidents.

• AI-native operations — agents, bounded automation, evals, with approvals and rollback — are part of how the lane runs, not a side experiment.