Michael L. Abramowitz

I designed and built the DevOps infrastructure for a neobank from scratch, creating the foundation for secure, reliable, and auditable delivery of customer-facing and internal banking services. I built CI/CD pipelines, automated AWS infrastructure provisioning, and created Kubernetes-based environments across separate AWS accounts to support isolation, governance, and environment separation. I also introduced ring-based deployment workflows to reduce release risk and improve control over production rollouts.

My work included setting up observability with logs, metrics, and alerts, hardening the infrastructure to meet security and compliance requirements, supporting incident response processes, and reducing manual operational work through automation and scripting. The project established a production-ready cloud platform for the neobank, improved deployment reliability, and gave engineering teams a scalable and secure foundation for delivering banking services with lower operational risk.

The technologies I used included AWS, Kubernetes, CI/CD, Infrastructure as Code, multi-account AWS architecture, ring deployments, observability, logging, metrics, alerting, automation, scripting, and security hardening.

I delivered DevOps infrastructure for an AI-driven KYC platform that processed identity verification, document analysis, and risk assessment workloads at scale. The company needed a secure and reliable cloud platform for sensitive customer data, ML-powered verification services, and production APIs.

I worked on CI/CD pipelines, AWS infrastructure automation, and Kubernetes environments deployed across separate AWS accounts to support security, isolation, and environment governance. I helped implement ring-based deployment workflows to reduce release risk and improve production rollout control. I also improved operational visibility through centralized logging, metrics, tracing, and alerting, making it easier for engineering and security teams to monitor APIs, background processing, and ML-driven verification workloads.

The project strengthened the reliability, scalability, and security posture of the KYC platform, while supporting production-grade operations for identity verification and compliance-sensitive services.

The technologies used included AWS, Kubernetes, CI/CD, Infrastructure as Code, multi-account AWS architecture, observability, centralized logging, metrics, tracing, alerting, and DevOps for AI/ML workloads.

I delivered a CI/CD and Kubernetes infrastructure solution for a data management/data fabric company that needed a more reliable way to deploy and operate its platform across isolated AWS environments. The project focused on improving deployment reliability, infrastructure automation, and operational visibility for services responsible for data integration, processing, storage, and secure access.

I built and maintained CI/CD pipelines, automated AWS infrastructure, and managed Kubernetes environments across multiple AWS accounts to support isolation, governance, and scalability. I also implemented and supported ring-based deployment workflows, improved observability through logs, metrics, tracing, and alerting, and helped increase the resilience of data pipelines, APIs, and core platform services.

The solution made the platform easier to operate in production, reduced deployment risk, and enabled engineering and security teams to better control distributed cloud environments.

The technologies used included AWS, Kubernetes, CI/CD, Infrastructure as Code, multi-account AWS architecture, observability, logging, metrics, tracing, and alerting.