▪ Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Applied Mathematics, or

a related quantitative discipline.

▪ Experience: 3–5 years of hands-on engineering experience in a collaborative, team-based

environment.

▪ Programming: Professional proficiency in Python, Java or a similar programming/scripting

language.

▪ Systems: Strong Unix/Linux fundamentals with the ability to troubleshoot application,

deployment, environment, and runtime issues.

▪ Methodology: Familiarity with SDLC practices, CI/CD delivery models, change management,

and Kubernetes-based deployments.

Key Responsibilities

▪ Assess on-prem hosts and perform discovery across business processes, CPU, memory, storage,

dependencies, and runtime patterns to determine migration readiness.

▪ Analyze workloads based on functionality, business criticality, resiliency requirements, and

interruption tolerance to determine appropriate cloud compute placement.

▪ Plan and provision required cloud infrastructure capacity to support migration, testing, and

production execution.

▪ Execute UAT and production parallel testing, compare outcomes, capture evidence, and

troubleshoot discrepancies through closure.

▪ Perform performance tuning and optimization to ensure migrated workloads are stable,

scalable, efficient, and production ready.

▪ Partner with application engineering, infrastructure, and platform teams to finalize migration

plans, release approach, validation criteria, and rollback considerations.

▪ Manage release readiness, execute production deployment activities, and complete post

release checkout and validation procedures.

▪ Support legacy on-premises host decommissioning after successful migration and validation.

▪ Design, enhance, and implement automation frameworks and AI-assisted solutions to enable

repeatable, efficient, large-scale cloud migrations.

▪ Document migration procedures, operational learnings, risks, and best practices to improve the

factory execution model.