Solution Architect - AI-Led Enterprise VMware Exit To AWS Cloud

 •Bachelors degree in Computer Science, Engineering, Information Systems, or a related field; advanced degree preferred.

•12+ years of technology architecture and engineering experience, including 5+ years designing enterprise AWS cloud migration, modernization, or data center exit solutions.

•Proven experience architecting large VMware or VMC exit programs covering discovery, assessment, target-state architecture, AWS foundations, migration waves, testing, cutover, stabilization, and decommissioning.

•Strong hands-on architecture experience across VMware estates, AWS landing zones, multi-account strategy, networking, identity, security, compute, storage, databases, observability, backup, disaster recovery, and cloud operations.

•Experience defining workload disposition and migration patterns including rehost, replatform, refactor, retire, retain, and repurchase.

•Experience applying AI, automation, analytics, and agentic capabilities to accelerate infrastructure and application discovery, dependency analysis, wave planning, code and configuration assessment, testing, migration execution, and evidence generation.

•Experience designing secure, resilient, compliant, and auditable solutions for regulated enterprises; insurance or financial services experience preferred.

•AWS Certified Solutions Architect Professional, AWS Migration, VMware, networking, security, or equivalent certifications preferred.

•Deep knowledge of AWS Organizations, Control Tower, IAM, VPC, Transit Gateway, Direct Connect, Route 53, EC2, EBS, S3, RDS, container services, CloudWatch, CloudTrail, Systems Manager, Backup, and disaster recovery patterns.

•Strong understanding of VMware vSphere, vCenter, ESXi, NSX, storage, backup, monitoring, licensing, and dependency considerations relevant to exit planning.

•Expertise in migration assessment, application dependency mapping, target platform selection, workload disposition, migration wave design, cutover architecture, rollback, resilience, and decommissioning controls.

•Proficiency in infrastructure-as-code and automation using Terraform, CloudFormation, scripting, APIs, CI/CD, configuration management, and policy-as-code.

•Working knowledge of AI/ML, Generative AI, Agentic AI, LLM-based analysis, model governance, Human-in-the-Loop validation, prompt and output controls, and auditability of AI-assisted decisions.

•Strong application, infrastructure, network, data, identity, security, privacy, compliance, observability, FinOps, and operational architecture skills.

•Ability to lead architecture workshops, document decisions and trade-offs, resolve cross-domain dependencies, and communicate effectively with executives, business owners, engineers, security teams, and vendors.