Lead architecture and technical strategy for migrating legacy and on-premises applications to AWS cloud.
Assess existing application architectures and codebases for cloud readiness and modernization opportunities.
Design scalable, secure, and automated migration solutions for full stack applications (front-end, back-end, data layers).
Implement application refactoring, re-platforming, or re-architecting efforts to leverage AWS native services (e.g., Lambda, ECS/EKS, RDS, DynamoDB).
Develop front-end and back-end architectures ensuring seamless integration and cloud compatibility.
Define cloud infrastructure using Infrastructure as Code (IaC) tools such as AWS CloudFormation, Terraform, or AWS CDK.
Create and maintain CI/CD pipelines for continuous integration and automated deployments, incorporating AI-powered code quality gates and automated security scanning.
Lead and mentor development teams on AI-native engineering practices, establishing standards for AI tool adoption and measuring productivity gains across modern development frameworks and backend technologies.
Collaborate with cross-functional teams including DevOps, security, QA, and product to ensure successful migration and operation.
Develop and enforce cloud migration best practices, security policies, and governance.
Evaluate and integrate agentic AI solutions into development and deployment workflows to drive automation and efficiency.
Identify and mitigate risks associated with migration activities.
Monitor migrated applications for performance, cost optimization, and security compliance on AWS.
Stay current with AWS migration tools, AI development tools, and cloud-native patterns to continuously improve approach.
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
7+ years of IT experience including extensive software development and application architecture.
Minimum 3 years of hands-on experience with AWS cloud solutions, focusing on application migration and modernization.
Daily proficiency with AI coding assistants (GitHub Copilot, Cursor, Claude Code, Codex, or Kiro) with demonstrated ability to improve team productivity through AI tool adoption.
Experience measuring and reporting AI-driven productivity improvements across engineering teams.
Familiarity with agentic AI frameworks including LangChain, Claude Agent SDK, and Bedrock Agent SDK, and their application in the SDLC.
Understanding of AI agents in development workflows (automated code review, deployment agents, testing agents).
Strong full stack development skills with front-end (React, Angular, Vue.js) and back-end (Node.js, Java, Python, .NET) frameworks.
Experience migrating monolithic, legacy, or on-premises applications to AWS (lift-and-shift, re-platforming, refactoring).
Deep knowledge of AWS services: EC2, Lambda, ECS/EKS, API Gateway, RDS, DynamoDB, S3, Cognito, CloudWatch, IAM.
Strong skills in Infrastructure as Code (CloudFormation, Terraform, CDK).
Proficient with containerization and orchestration (Docker, Kubernetes, AWS ECS/EKS).