Exploring Technology.
Building the Future.

My background is in platform engineering, site reliability engineering, cloud infrastructure and database systems, with much of my experience gained in financial-services environments. I work across Azure, automation, observability, CI/CD, data platforms and production support, often on systems where resilience, control and performance really matter.

A growing part of my work is focused on AI-ready platforms. I am interested in how cloud, data and AI can be brought together in a practical way: not just experimenting with new tools, but building the infrastructure, pipelines and operating model needed to make AI services reliable and useful. My experience with Azure AI Foundry, Databricks, data engineering, automation and platform reliability gives me a strong foundation for supporting AI-enabled applications and analytics platforms.

I approach AI from an engineering and platform perspective. That means thinking about how data is collected, processed, secured and made available; how AI services are deployed and monitored; how teams can experiment safely; and how intelligent systems can be integrated into real business workflows. For me, successful AI is not only about the model — it is also about the platform, data quality, governance, monitoring and operational reliability around it.

Much of my cloud work is based on Microsoft Azure. I design and maintain platforms using tools such as Azure DevOps, Terraform, Kubernetes, Databricks, Azure Synapse, Azure Data Factory, Azure AI Foundry and Azure monitoring services. I use automation to make infrastructure easier to deploy, manage and repeat consistently.

I also have strong experience in observability and reliability. I build dashboards, alerts and monitoring solutions using tools such as Grafana, Prometheus, Loki, Thanos, Azure Monitor and Log Analytics. This helps teams understand how their systems are performing, respond quickly to incidents and reduce recurring operational problems.

Data platforms are another important part of my experience. I have worked extensively with SQL Server, PostgreSQL, Azure SQL and data warehousing technologies. This gives me a strong understanding of how data systems behave in production, from performance and availability through to backup, recovery and long-term maintainability.

More recently, I have worked on cloud-based research, trading and ETL platforms using technologies such as Airflow, Databricks, Kubernetes and PostgreSQL. This has involved designing data pipelines, supporting workflow orchestration and helping teams build platforms that are practical, scalable and reliable.

I enjoy working where cloud infrastructure, data engineering, AI and software delivery meet. My approach is pragmatic: build systems that work in the real world, automate what can be automated, make problems visible, and design platforms that teams can trust.