Building resilient, scalable cloud infrastructure with a passion for automating complexity and leveraging AI to drive efficiency.
Hello! I'm a dedicated and results-driven Cloud DevOps Engineer with a deep specialization in artificial intelligence and machine learning infrastructure. My expertise lies in designing, building, and maintaining robust, scalable, and secure cloud environments that serve as the backbone for cutting-edge AI applications.
With a strong foundation in both software development and systems administration, I bridge the gap between development and operations, fostering a culture of collaboration and efficiency. I am passionate about Infrastructure as Code (IaC), containerization technologies like Docker and Kubernetes, and building CI/CD pipelines that accelerate development cycles while ensuring stability.
My goal is to empower development teams by providing them with the tools and platforms they need to innovate rapidly and reliably. I thrive on solving complex problems and am constantly exploring new technologies to push the boundaries of what's possible in the world of AI and cloud computing.
Partnering with teams to design, build, and operate cloud platforms and intelligent applications that deliver business value from day one.
A snapshot of the tools and technologies I use to build and deploy modern applications.
A curated selection of cloud foundations, migrations, AI platforms, MLOps, CI/CD, and data-platform delivery across Azure, AWS, and Google Cloud.
Microsoft Azure
A backend-focused Azure architecture connecting separate application services to private data, containers, retrieval, document processing, secrets, and observability.
Amazon Web Services
A controlled migration blueprint for moving a web platform between AWS accounts while making infrastructure, data, certificate, DNS, compute, and cutover dependencies explicit.
Google Cloud
A controlled Google Cloud MLOps loop for repeatable model training, evaluation, artifact handling, telemetry, and promotion decisions.
Technical articles on cloud operations, Kubernetes, delivery pipelines and application security, published under my byline.
I trace a tenant-isolation failure to the PostgreSQL role that owned the tables, and explain how to test row-level security with the application’s actual runtime identity.
I examine why Kubernetes Secret synchronization left two pods with different process environments, and show how a deployment check verifies required variable names in every pod.
I describe consolidating duplicate Azure DevOps delivery definitions with run parameters, build tags and stage conditions, including the routing checks that keep modules separate.
Recorded conference talks and guest conversations about database delivery, cloud security, AI agents and DevOps.
A guest discussion of AWS AI services, token costs, sovereign cloud controls and the effect of agent automation on engineering work.
I discuss typed tools, separate read and execution identities, short-lived credentials and approval controls for AI agents that operate cloud infrastructure.
Industry-recognized credentials that demonstrate my ability to build, secure, and scale cloud-native platforms across Azure, AWS, and Google Cloud.
Have a question, a project proposal, or just want to connect? Feel free to send me a message. I'm always open to discussing new opportunities and collaborations.
