Senior Cloud Solutions Architect

Designing multi-account strategies with AWS Organisations, architecting complex serverless applications (Lambda, API Gateway, Step Functions), implementing robust DR patterns, and troubleshooting deep cloud issues.

Authoring reusable, modular, and version-controlled Terraform code for complex infrastructure deployments. Implementing state locking, managing dependencies, and mentoring others on IaC best practices.

Designing and deploying production-grade Kubernetes clusters (EKS, GKE, AKS). Managing Helm charts, Ingress controllers, and service meshes (e.g., Istio). Troubleshooting cluster performance and scaling issues.

Creating custom dashboards and complex alerts. Implementing distributed tracing and APM to diagnose performance bottlenecks in microservices architectures. Defining SLOs/SLIs for critical services.

Designing and building complex, multi-stage CI/CD pipelines from scratch, including security scanning (SAST/DAST), automated testing gates, and deployment strategies (e.g., blue/green, canary).

Creating detailed, multi-layer architecture diagrams that communicate complex systems effectively. Using tools like `diagrams.py` to automate diagram generation and keep documentation in sync with reality.

• Engineering Leads and Teams (they're building what you design)
• Product Managers (they define what needs to be built)
• Security Operations (they'll scrutinise your designs)
• Finance Business Partners (they care about the cloud bill)
• Other Senior Architects (for peer review and collaboration)

• Cloud Provider Account Teams (AWS, Azure, GCP)
• Key Technology Vendors (e.g., for specific tooling)
• External Auditors (occasionally, for compliance checks)

Security threats are constantly evolving, and traditional perimeter-based security is no longer enough. You'll need to design architectures that assume breach and implement 'Zero Trust' principles, where every request is authenticated and authorised, regardless of its origin.

Micro-segmentation and network isolation strategie · Identity-centric security (e.g., OIDC, OAuth2, fin · Secrets management and rotation automation (e.g., · Security posture management and automated complian · Supply chain security for IaC and container images

• This week: Deep-dive into a specific cloud security service you use less often (e.g., AWS WAF, Security Lake).
• This month: Design a Zero Trust architecture for a new application, focusing on identity and least privilege.
• Month 2: Implement automated security scanning (SAST/DAST) into a CI/CD pipeline you own.
• Month 3: Lead a 'threat modelling' exercise for a critical system.

Quick win: Review the IAM policies for your current projects. Are they truly 'least privilege'? Probably not. Start tightening them up.

AI and Machine Learning are no longer niche; they're becoming integrated into every aspect of business. As an architect, you'll need to understand how to design the underlying infrastructure to support ML workloads, manage the ML lifecycle, and integrate AI services securely and efficiently.

Data pipelines for ML (feature stores, data versio · Compute infrastructure for training and inference · MLOps platforms and tools (e.g., SageMaker, Kubefl · Model deployment strategies (batch, real-time, edg · Ethical AI and responsible ML considerations in de

• This week: Read up on a major cloud provider's ML services (e.g., AWS SageMaker, Azure ML).
• This month: Design a conceptual MLOps pipeline for a simple ML model.
• Month 2: Build a small PoC for deploying an ML model using a serverless function or container.
• Month 3: Collaborate with a Data Scientist to understand their infrastructure needs and pain points.

Quick win: Explore the pre-built AI services offered by your primary cloud provider (e.g., AWS Rekognition, Comprehend). Understand their APIs and how they could be integrated into an application.