Editable, ATS-safe résumé templates you can download as PDF, Word, or Google Docs — or the raw Markdown — then make your own. One for each of the three tracks this bootcamp maps to, written for an engineer with roughly three to four years behind them and shaped from two sources: what the classes teach, and what current Azure, cloud, and DevOps postings actually ask for. Not blank forms — the argument, pre-shaped, with a real experience section to adapt.
[BRACKET], and delete lines that don't fit you.Ctrl/⌘V to paste it in, formatting intact.[BRACKETS] for your real numbers.The full-spine résumé — the one written for the composite job posting on the landing page. Leads with the end-to-end platform and balances infrastructure, delivery, and operations. Start here if you want the broadest set of postings to say yes.
# [YOUR NAME] Cloud Engineer — Azure [City, Country] | [email@address] | [phone] GitHub: github.com/[you] | LinkedIn: linkedin.com/in/[you] ## Summary Azure cloud engineer with ~4 years designing, building, and operating cloud infrastructure — infrastructure as code, secure CI/CD, private networking, and cost-aware architecture. Ships production estates scoped from Microsoft reference architectures and defends them against the five Well-Architected pillars. Microsoft Certified: Azure Administrator Associate (AZ-104); Azure Solutions Architect Expert (AZ-305) in progress. ## Technical Skills - Azure core: Virtual Networks, subnets, NSGs, private endpoints, App Service, VM Scale Sets, Azure Storage (LRS/ZRS/GRS), Azure SQL, Cosmos DB, Front Door, Application Gateway (WAF) - Identity and governance: Microsoft Entra ID, RBAC, managed identities, Conditional Access, Azure Policy (deny/DeployIfNotExists), management groups - Infrastructure as Code: Terraform (remote state, modules, for_each, drift detection), Bicep (modules, what-if, deployment scopes) - CI/CD: GitHub Actions and Azure Pipelines, OIDC workload identity federation (no stored secrets), gated environments, blue-green and canary releases - Containers and Kubernetes: Docker, Azure Container Registry, Azure Container Apps, AKS (kubectl, Deployments, ingress, workload identity) - Observability: Azure Monitor, Log Analytics, KQL, Application Insights, alerting - Security: Key Vault, Defender for Cloud, private connectivity, least privilege - Cost / FinOps: Cost Analysis, budgets, reservations vs savings plans, right-sizing, tagging - Scripting: Azure CLI, PowerShell, Python, Bash ## Experience Cloud Engineer, [Company] — [Mon 20XX – Present] - Moved [N] Azure workloads onto reusable Terraform modules and OIDC-federated GitHub Actions, removing every stored deployment secret (gh secret list returns empty) and cutting release time from [X] to [Y]. - Designed hub-and-spoke networking with private endpoints and private DNS so [system]'s data tier is unreachable from the public internet; delivered from design doc to production with zero downtime. - Reduced monthly Azure spend by ~[N]% through right-sizing, moving the flat compute floor to reservations, and adding budget guardrails with forecast alerts — reviewed monthly, not once a year. - Owned observability for [team]: KQL workbooks, symptom-based alerts, and an on-call runbook that cut mean time to restore from [X] to [Y]. [Prior role — e.g. Cloud Support Engineer / Systems Administrator], [Company] — [Mon 20XX – Mon 20XX] - Administered Microsoft Entra ID and Azure RBAC for [N] users and groups; automated onboarding, access reviews, and reporting in PowerShell, removing [hours]/week of manual work. - Supported and migrated on-prem workloads to Azure (VMs, storage, backup and restore), writing the runbooks the team still uses. ## Projects (portfolio — github.com/[you]) Enterprise Web Platform — scoped from Microsoft's baseline reference architecture: Application Gateway with WAF fronting a private App Service and Azure SQL, secrets in Key Vault read by managed identity, shipped through a gated OIDC pipeline. README walks a reviewer from the public URL to a private row. Governed Landing Zone — a management-group hierarchy, deny/modify policies for regions and tags, hub-and-spoke with private DNS, and centralised logging by policy — all as code, so nothing lands ungoverned. AI Workload — an Azure OpenAI assistant reachable only through a private endpoint, metered per caller at an API Management gateway, with token spend on a dashboard. ## Decisions and Trade-offs - Chose Bicep for the Azure-only estate (native tooling, no state to secure) and Terraform where a multi-cloud requirement was real — not by habit. - Chose Container Apps over AKS until a workload genuinely needed the Kubernetes surface and the team could staff cluster operations. ## Certifications - Microsoft Certified: Azure Administrator Associate (AZ-104) — [Year] - Microsoft Certified: Azure Solutions Architect Expert (AZ-305) — in progress - Microsoft Certified: Azure Fundamentals (AZ-900) — [Year] ## Education [Degree or relevant training], [Institution] — [Year]
Reweighted toward AZ-104: core infrastructure, identity and governance, networking, monitoring, and cost. Leads with the Landing Zone project. Start here if the postings you want say "administer," "operate," and "govern" more than "build."
# [YOUR NAME] Azure Administrator [City, Country] | [email@address] | [phone] GitHub: github.com/[you] | LinkedIn: linkedin.com/in/[you] ## Summary Azure administrator with 3+ years operating and governing Azure estates — identity, networking, storage, monitoring, backup, and cost — and comfortable expressing infrastructure and policy as code. Microsoft Certified: Azure Administrator Associate (AZ-104); Azure Solutions Architect Expert (AZ-305) in progress. ## Technical Skills - Identity and access: Microsoft Entra ID, RBAC, managed identities, Conditional Access, PIM, access reviews - Governance: Azure Policy (deny and DeployIfNotExists), management groups, tagging standards, resource organization - Networking: Virtual Networks, subnets, NSGs, private endpoints, private DNS, VPN Gateway, hub-and-spoke - Compute and storage: Virtual Machines, scale sets, App Service, Azure Storage (LRS/ZRS/GRS), Azure SQL, backup and restore - Backup and DR: Recovery Services vault, Azure Backup, Site Recovery, RPO/RTO planning - Monitoring: Azure Monitor, Log Analytics, KQL, diagnostic settings, alerts and action groups - Cost management: Cost Analysis, budgets, reservations, right-sizing - Automation: Azure CLI, PowerShell, Bicep ## Experience Azure Administrator, [Company] — [Mon 20XX – Present] - Govern an estate of [N] subscriptions with a management-group hierarchy and Azure Policy: deny for disallowed regions, modify to inherit cost-center tags — so nothing is created ungoverned or untagged. - Cut monthly spend ~[N]% by reserving the measured flat floor of compute, right-sizing on Advisor data, and standing up budgets with forecast alerts. - Own backup and recovery: Recovery Services vault policies and tested restores against a [X]-hour RTO / [Y]-minute RPO. - Replaced [N] noisy alerts with three symptom-based ones and KQL workbooks the on-call team actually reads. [Prior role — e.g. Systems Administrator / IT Support], [Company] — [Mon 20XX – Mon 20XX] - Managed Microsoft Entra ID users, groups, and RBAC for [N] staff; automated joiner/mover/leaver in PowerShell. - Ran patching, backup, and monitoring for on-prem and hybrid workloads; led the lift-and-shift of [system] to Azure. ## Projects (portfolio — github.com/[you]) Governed Landing Zone — a governed Azure estate from the Cloud Adoption Framework: management-group hierarchy, deny/modify policies, hub-and-spoke with private DNS, centralised logging by DeployIfNotExists — all as code. Observability and Cost Guardrails — centralised telemetry by policy, three owned alerts (not forty ignored), and a budget with a forecasted threshold, over a multi-resource estate. Private Web Application — a two-tier app with storage unreachable from the internet: private endpoint, private DNS, public access disabled, keyless managed-identity access, with an evidence runbook. ## Decisions and Trade-offs - Enforced tags with a modify policy inheriting cost-center from the resource group, rather than denying every untagged resource — enforcement that does not teach people to type "tbd". - Reserved only the measured flat floor of compute; left spiky workloads on pay-as-you-go. ## Certifications - Microsoft Certified: Azure Administrator Associate (AZ-104) — [Year] - Microsoft Certified: Azure Solutions Architect Expert (AZ-305) — in progress - Microsoft Certified: Azure Fundamentals (AZ-900) — [Year] ## Education [Degree or relevant training], [Institution] — [Year]
Weighted toward Phase Three: Git, infrastructure as code, GitHub Actions federated to Azure, containers, and pipelines. Leads with the GitOps loop and the AI workload's delivery story. Start here if the postings emphasise CI/CD, automation, and "you build it, you run it."
# [YOUR NAME] DevOps Engineer — Azure [City, Country] | [email@address] | [phone] GitHub: github.com/[you] | LinkedIn: linkedin.com/in/[you] ## Summary DevOps engineer with ~4 years shipping Azure infrastructure through reviewed, secret-free pipelines — Git, infrastructure as code, GitHub Actions and Azure Pipelines federated by OIDC, containers, and observability. Microsoft Certified: DevOps Engineer Expert (AZ-400) and Azure Administrator Associate (AZ-104). ## Technical Skills - CI/CD: GitHub Actions (reusable workflows, matrices, environments), Azure Pipelines (YAML, stages, approvals, gates), package feeds (Azure Artifacts, SemVer) - Secure delivery: OIDC workload identity federation (no stored secrets), branch protection, CODEOWNERS, pipeline least privilege - Release strategy: blue-green, canary, ring-based rollouts, feature flags (App Configuration Feature Manager) - Infrastructure as Code: Terraform (remote state, modules, for_each, drift), Bicep (modules, what-if) - Containers and Kubernetes: Docker, Azure Container Registry, Azure Container Apps, AKS, image scanning - DevSecOps: SAST/DAST, dependency and IaC scanning, secret scanning, Defender for Cloud, policy-as-code - Source control: Git (trunk-based and GitFlow), pull-request review, semantic versioning - Observability: Azure Monitor, Log Analytics, KQL, Application Insights, alerting - Scripting: Bash, PowerShell, Python; Azure CLI ## Experience DevOps Engineer, [Company] — [Mon 20XX – Present] - Built the delivery loop for [N] services: PR runs a what-if plan and full test suite, merge deploys to non-prod, a human-gated prod stage, OIDC auth with zero stored secrets — deploy frequency up from [X] to [Y], change-fail rate down. - Added shift-left security to every pipeline (dependency, IaC, secret, and image scanning), turning findings into gated quality checks rather than ignored reports. - Introduced canary releases with App Configuration feature flags, decoupling deploy from release and cutting rollback time to [minutes]. - Cut CI minutes ~[N]% with build caching, matrices, and reusable workflows. [Prior role — e.g. Build/Release Engineer / Systems Administrator], [Company] — [Mon 20XX – Mon 20XX] - Migrated classic release pipelines to YAML and federated the riskiest secret-bearing service connection first — migration by risk, not by crusade. - Automated environment builds and routine ops in PowerShell and Bash, removing [hours]/week of manual toil. ## Projects (portfolio — github.com/[you]) The GitOps Loop — a full delivery loop: PR-triggered what-if, merge-to-nonprod, human-gated production, OIDC with an empty gh secret list. No one deploys by clicking. AI Workload delivery — an Azure OpenAI assistant's whole infrastructure through one pipeline: private endpoint, keyless identity, API Management metering tokens per caller, spend dashboard. Enterprise Web Platform — a zone-redundant three-tier app delivered through a gated pipeline with deployment slots for zero-downtime releases and telemetry from day one. ## Decisions and Trade-offs - Converted classic release pipelines to YAML only when touched, and federated the riskiest secret-bearing service connection first — migration by risk, not by crusade. - Used self-hosted runners only where a private-network reach demanded it, with the same patching and least-privilege discipline as production. ## Certifications - Microsoft Certified: DevOps Engineer Expert (AZ-400) — [Year] - Microsoft Certified: Azure Administrator Associate (AZ-104) — [Year] - Microsoft Certified: Azure Fundamentals (AZ-900) — [Year] ## Education [Degree or relevant training], [Institution] — [Year]
Where these come from: the résumé philosophy behind every line — consequence bullets, honest tenure, the decisions-and-trade-offs section — is taught in Class 42, Landing the Job. The three projects they reference are the capstone plates; build those, and the Projects section fills itself with things a reviewer can actually clone. Then rehearse the questions on the interview page and walk in with a plan for your first ninety days.