[CMC] Cloud Solutions Architect

Job Description

Project – the aim you’ll have

You will join the AWS cloud practice, supporting changing international client engagements across platform engineering, cloud architecture, migrations, data platforms, AI-enabled systems and production cloud environments. The role is AWS-first, but many projects require multi-cloud thinking, especially Azure exposure, Kubernetes, Terraform, CI/CD, security, observability and close cooperation with engineering and client teams.

Position – how you’ll contribute

• Design secure, scalable and cost-effective AWS cloud architectures.
• Define architecture standards for Kubernetes, IaC, CI/CD, networking and observability.
• Support multi-cloud solutioning, especially where AWS integrates with Azure-based environments.
• Review Terraform, platform components, deployment pipelines and architecture decisions.
• Guide engineers in translating client requirements into production-ready designs.
• Support discovery, estimations, risk assessment and technical proposal work.
• Drive cloud security, reliability, operability and production-readiness practices.
• Mentor engineers and act as a technical advisor for clients and delivery teams.

Qualifications

Expectations – the experience you need

• Strong experience as Cloud Architect, Platform Architect or Lead Cloud Engineer.
• Deep AWS knowledge, including IAM, VPC, compute, storage, databases, EKS and security.
• Practical experience with at least one other cloud platform (preferably Azure).
• Hands-on experience with Terraform and Infrastructure as Code standards.
• Strong understanding of Kubernetes, containers and cloud-native platform design.
• Experience designing CI/CD, environment promotion and production release models.
• Ability to design secure, observable and maintainable distributed systems.
• Strong communication skills and the ability to collaborate effectively with both technical and business stakeholders.

Additional skills – the edge you have

• Experience with Azure DevOps, AKS, Microsoft Fabric or Azure AI services.
• Familiarity with AI/LLM platforms, RAG, API gateways or authorization-aware systems.
• Experience in regulated, financial, data-heavy or integration-heavy environments.

Additional Information