Cloud Architect CV (ATS-Optimised) — Complete Guide for British CVs

Cloud Architect with experience designing secure, scalable platforms across AWS and Azure (and exposure to GCP), translating business constraints into production architectures. Certified at senior level (AWS Solutions Architect Professional and/or Azure Solutions Architect Expert) and able to explain trade-offs clearly to engineering, security, and delivery stakeholders. Delivered migrations and modernisation using Terraform for Infrastructure as Code, Kubernetes for container orchestration, and managed services such as AWS Lambda and Azure Functions for event-driven workloads. Focus areas include measurable reliability (targeting 99.9%+), cost optimisation (e.g., reducing infra spend by 25–35%), and governance through repeatable patterns.

Known for building architecture “guardrails” that speed up delivery without sacrificing security, including IAM least privilege, network segmentation via VPC/VNet, and encryption for data in transit and at rest. Use monitoring and incident tooling to drive resilience, typically combining CloudWatch/Azure Monitor, log aggregation, and alerting strategies that reduce mean time to recovery (MTTR). Translate system constraints into engineering roadmaps using design documents, threat models, and dependency mapping across application teams. Bring structured communication using RFCs and architecture decision records so changes remain auditable across multi-team programmes.

Led a cloud migration programme moving 50+ on-prem workloads to AWS, prioritising low-risk cutovers and measurable outcomes for availability and cost. Architected serverless microservices on Lambda and API gateways, containerised workloads on EKS, and data services using S3 and RDS with automated backups and lifecycle policies. Delivered the platform using Terraform modules, with CI/CD-driven deployments and environment promotion, and implemented IAM policies and VPC routing to enforce separation of duties. KPI results included a 35% reduction in infrastructure cost (£800K/year spend), improved deployment frequency by 2–3x, and achieved 99.95% availability during peak usage windows.

Designed and implemented a Kubernetes landing zone that enabled secure self-service for application teams while maintaining central governance. Standardised namespaces, RBAC, ingress patterns, and secrets handling, leveraging Helm for repeatable releases and integrating with container registries for controlled image provenance. Built operational readiness through runbooks, SLOs, and monitoring dashboards using CloudWatch or Azure Monitor, enabling faster troubleshooting and reduced MTTR. Delivered a hybrid integration approach using secure connectivity and well-defined network paths, supporting regulated data flows with encryption, audit logging, and policy checks aligned to organisational compliance requirements.

Create production-grade Infrastructure as Code with Terraform, including reusable module design, environment separation, and safe state management strategies. Implemented policy-aware deployments using tagging standards, variable validation, and CI/CD checks to prevent configuration drift and insecure changes reaching production. Integrated pipeline tooling such as GitHub Actions or Azure DevOps to run plan/apply workflows, security scanning, and automated testing for infrastructure changes. This approach reduced manual intervention, improved change traceability, and supported faster recovery from failed releases through controlled rollbacks and predictable rollouts.

Applied automation to manage lifecycle operations such as scaling policies, automated backups, log retention, and secret rotation, with an emphasis on operational reliability. Used best-practice patterns for networking (VPC/VNet components, subnets, route tables), compute sizing, and managed service configuration to avoid over-provisioning. Coordinated with application engineering to standardise deployment patterns for microservices, including health checks, autoscaling triggers, and zero-downtime strategies. Ensured visibility using dashboards and alerting rules tied to service-level indicators, supporting incident response with actionable telemetry rather than ad-hoc investigation.

Designed secure architectures covering identity, access, and network controls, with IAM/RBAC implemented using least-privilege roles and scoped permissions. Built network segmentation using VPCs/VNet design, private subnets, controlled routing, and ingress/egress controls to minimise blast radius. Where required, integrated web application protection such as AWS WAF and DDoS controls, and enforced encryption using managed key strategies for data in transit and at rest. Ensured auditability through centralised logs, retention policies, and consistent tagging so governance reporting remains straightforward across accounts/subscriptions.

Conducted threat modelling and security reviews for new architecture proposals, translating findings into concrete engineering requirements for teams. Partnered with security and compliance stakeholders to align controls with GDPR-aligned practices and organisational policy expectations, including data handling standards and access review processes. Embedded security into delivery by defining secure-by-default templates and validating infrastructure changes through automated checks. Measured outcomes through improved access hygiene, reduced privilege escalation risk, and quicker incident investigation due to richer context from monitoring and log correlation.

Established observability baselines for production systems, using CloudWatch/Azure Monitor and structured logging to ensure teams could diagnose issues quickly and confidently. Implemented alerting aligned to SLOs and error budgets, covering latency, throughput, error rates, and saturation signals for both API layers and background workers. Standardised dashboards by service, environment, and dependency, helping reduce the time spent correlating events across systems. Used runbooks and post-incident reviews to improve operational maturity, often decreasing MTTR through clearer diagnostics and automated recovery mechanisms.

Built resilience into architectures via autoscaling policies, circuit breakers, retry strategies, and safe deployment approaches for microservices. Used health checks, graceful shutdown logic, and controlled rollouts to minimise customer impact during releases. Documented operational procedures for common failures such as database throttling, queue backlogs, and networking misconfigurations. Maintained readiness through regular game-days and simulations, ensuring teams could respond effectively to outages with known telemetry and pre-agreed mitigation steps.