Senior Cloud Architect

We are seeking a Senior Cloud Architect to define, evolve, and oversee the cloud architecture supporting a suite of enterprise applications. This role will ensure the infrastructure is secure, scalable, and reusable enabling product teams to deliver applications and data products that meet enterprise standards. From real-time data processing to AI/ML solutions, you will design a platform that scales with business needs.

Key Responsibilities

Lead Cloud Architecture

• Design AWS-native infrastructure patterns supporting multiple applications and workstreams.
• Define and maintain reference architectures, Infrastructure as Code (IaC) modules, and CI/CD standards for consistent adoption.
• Implement modular and composable architecture enabling shared services and observability tools across domains.

Embed Security, Scalability, and Resilience

• Apply AWS best practices for security, performance, and cost optimization.
• Implement autoscaling, event-driven compute, and fault-tolerant designs for high-load events.
• Ensure compliance with enterprise security, availability, and recoverability standards.

Collaborate Across Teams

• Partner with platform engineers and DevOps to implement shared infrastructure services.
• Advise product teams on infrastructure design and remove environment blockers.
• Collaborate with data and ML engineering teams to deliver scalable pipelines and ML workloads.

Drive Enablement and Governance

• Maintain infrastructure documentation, templates, and onboarding guides.
• Represent architecture decisions in cross-team forums to align and share best practices.
• Embed governance practices including security, tagging, and resource accountability in IaC.

Required Skills & Experience

1. Cloud Architecture Depth 7+ years designing AWS-native platforms using Lambda, Step Functions, DynamoDB, AppSync, S3, Cognito, and other AWS services.
2. Modern Engineering Practices 7+ years delivering infrastructure with CI/CD tools (GitHub Actions, AWS CodePipeline), Infrastructure as Code (Terraform, CDK), and GitOps.
3. Data & ML Infrastructure 7+ years supporting data-intensive applications and AI/ML platforms (e.g., MLFlow, SageMaker, Databricks, feature stores).