Senior AWS Migration Engineer

EPAM Systems; Chennai District; Sur place; INR 7 000 000 - 11 000 000; Plein temps

Résumé du poste

EPAM Systems is seeking a Senior AWS Migration Engineer with Gen AI to lead modernization of on-premise applications on AWS with secure, cost-aware designs. You will drive migration planning and delivery using AWS migration tools, IaC, and CI/CD while applying Gen AI capabilities across cloud workloads.

The role requires 5-8 years of cloud engineering and migration experience, deep AWS service knowledge, and hands-on experience with migration tools and IaC.

Qualifications

• 5-8 years of professional cloud engineering and migration experience.
• Strong expertise with AWS compute, storage, database, networking, and security services.
• Hands-on migration using AWS migration tools and IaC.
• Experience building scalable, secure, cost-optimized cloud architectures.

Responsabilités

• Lead full-lifecycle migrations of on-prem apps to AWS using rehost, replatform, and refactor paths.
• Assess current infrastructure, map dependencies, and shape migration approach.
• Design scalable AWS architectures balancing security, performance, and cost.
• Execute migrations with MGN, DMS, DataSync, and Snowball.
• Build infrastructure via Terraform or CloudFormation (IaC).
• Automate build and release workflows with GitLab CI, Jenkins, and CodePipeline.
• Implement observability with CloudWatch, CloudTrail, and Prometheus.
• Integrate AI/ML features into cloud workloads and Gen AI capabilities.
• Drive DevOps and migration automation with AI-enabled approaches.

Connaissances

Cloud engineering

AWS expertise

CI/CD automation

Infrastructure as Code

Migration strategy

Outils

Terraform

CloudFormation

GitLab CI

Jenkins

CodePipeline

MGN

DMS

DataSync

Snowball

Description du poste

We are looking for a Senior AWS Migration Engineer with Gen AI to modernize on-prem applications on AWS with secure, cost-aware designs. You will lead migration planning and delivery using AWS migration tools, IaC, and CI/CD while applying Amazon Bedrock, SageMaker, and OpenAI APIs to cloud workloads.

Responsibilities

• Lead full-lifecycle migrations of on-prem applications to AWS using Rehost, Replatform, and Refactor paths
• Assess current infrastructure, map dependencies, and shape the migration approach
• Design scalable AWS architectures that balance security, performance, and cost optimization
• Execute hands-on migrations with AWS Application Migration Service (MGN), AWS Database Migration Service (DMS), AWS DataSync, and Snowball
• Build and maintain cloud infrastructure through Terraform or CloudFormation (Infrastructure as Code)
• Automate build and release workflows using GitLab CI, Jenkins, and CodePipeline
• Implement observability using CloudWatch, CloudTrail, and Prometheus for monitoring and logging
• Integrate AI/ML features into cloud workloads for chatbots, automation, and data insights
• Apply Generative AI capabilities using Amazon Bedrock, SageMaker, and OpenAI APIs
• Drive DevOps and migration automation using AI-enabled approaches

Requirements

• Proven 5-8 years of professional experience in cloud engineering and migration initiatives
• Deep expertise with AWS compute services such as EC2, Lambda, and ECS/EKS
• Hands-on experience with AWS storage offerings including S3, EBS, and EFS
• Solid knowledge of AWS database services like RDS, Aurora, and DynamoDB
• Strong background in AWS networking across VPC, VPN, and Direct Connect
• Practical understanding of AWS security services including IAM, KMS, and Secrets Manager
• Demonstrated experience with AWS migration tools such as MGN, DMS, and DataSync/Snowball
• Proficiency in Infrastructure as Code using Terraform or CloudFormation
• Working knowledge of CI/CD tools including GitLab CI, Jenkins, and CodePipeline
• Familiarity with monitoring and logging tools such as CloudWatch, CloudTrail, and Prometheus
• Basic to intermediate exposure to Generative AI services including Amazon Bedrock, SageMaker, and OpenAI APIs
• Knowledge of prompt engineering and LLM-based application use cases