Cloud Solutions Architect

Anblicks

$145K — $175K *
Enterprise Technology
11 - 15 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related field.
  • 12+ years in Cloud Engineering, Platform Engineering, DevOps, SRE, or Infrastructure Engineering.
  • 5+ years leading cloud/platform engineering teams.
  • Strong experience with AWS, Azure, GCP, or multi-cloud environments.
  • Hands-on expertise in Kubernetes, Infrastructure as Code, CI/CD, cloud networking, observability, and security.
  • Experience building and operating enterprise-scale cloud platforms.
  • Experience enabling AI/ML or Generative AI platforms within cloud environments.

Responsibilities

  • Build and support enterprise AI platform capabilities including GenAI and AI development services.
  • Enable secure access to platforms such as Azure AI and AWS Bedrock.
  • Establish governance, security, and cost controls for AI workloads.
  • Accelerate adoption of AI-assisted engineering and business solutions.
  • Define and execute the cloud platform strategy and roadmap.
  • Establish cloud architecture standards and engineering best practices.
  • Build self-service platform capabilities for application teams.

Benefits

  • Opportunity to lead cutting-edge AI initiatives in cloud environments.
  • Collaborative work with cross-functional teams including application, security, and product personnel.
  • Access to professional development through cloud-related leadership and engineering practices.
  • Focus on both innovation and optimization within cloud and AI platforms.
Full Job Description
Cloud Solutions Architect

Role Summary

Lead the strategy, engineering, and operations of the enterprise cloud platform. Responsible for enabling secure, scalable, and cost-effective cloud infrastructure, platform services, automation, developer productivity, and AI platform capabilities.

Key Responsibilities

AI Platform Enablement
  • Build and support enterprise AI platform capabilities including GenAI, LLM, and AI development services.
  • Enable secure access to platforms such as Azure AI, Azure OpenAI, AWS Bedrock, Vertex AI, and similar services.
  • Establish governance, security, and cost controls for AI workloads.
  • Accelerate adoption of AI-assisted engineering and business solutions.

Cloud Platform Leadership
  • Define and execute the cloud platform strategy and roadmap.
  • Establish cloud architecture standards, governance, and engineering best practices.
  • Lead modernization and adoption of cloud-native technologies.

Platform Engineering & Automation
  • Build self-service platform capabilities for application teams.
  • Drive Infrastructure as Code (Terraform, CloudFormation, Pulumi) and automation initiatives.
  • Improve developer experience through platform engineering and CI/CD capabilities.

Cloud & Kubernetes Operations
  • Lead enterprise container and Kubernetes platform initiatives.
  • Ensure platform reliability, scalability, observability, and disaster recovery readiness.
  • Implement SRE practices and operational excellence frameworks.

Security, Governance & FinOps
  • Implement cloud security, compliance, and governance controls.
  • Drive cloud and AI cost optimization through FinOps practices.
  • Establish operational metrics, SLOs, and platform performance KPIs.

Leadership & Stakeholder Management
  • Lead teams of cloud engineers, platform engineers, DevOps, and SRE professionals.
  • Partner with application, security, data, and product teams.
  • Communicate platform strategy and investment priorities to senior leadership.


Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, or related field.
  • 12+ years in Cloud Engineering, Platform Engineering, DevOps, SRE, or Infrastructure Engineering.
  • 5+ years leading cloud/platform engineering teams.
  • Strong experience with AWS, Azure, GCP, or multi-cloud environments.
  • Hands-on expertise in Kubernetes, Infrastructure as Code, CI/CD, cloud networking, observability, and security.
  • Experience building and operating enterprise-scale cloud platforms.
  • Experience enabling AI/ML or Generative AI platforms within cloud environments.


Preferred Qualifications
  • Experience building Internal Developer Platforms (IDP).
  • Experience with Azure OpenAI, Azure AI Services, AWS Bedrock, Vertex AI, OpenAI, or Anthropic.
  • Knowledge of DevSecOps, SRE, Platform Engineering, and FinOps practices.
  • Cloud certifications from AWS, Azure, or Google Cloud.

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