George – AWS, GCP, Kubernetes

A Business Continuity Planning (BCP) platform that automates disaster recovery simulation, testing, and compliance evidence generation, helping organizations validate resilience strategies and meet regulatory requirements.

• Co-founded and helped shape the product strategy, architecture, and technical direction of the platform;
• Developed solutions for automated disaster recovery simulation, testing, and compliance evidence generation;
• Collaborated on product development, infrastructure, and operational processes to support platform growth and reliability.

A cloud-native platform engineering consultancy helping AI and software companies build scalable, secure, and cost-efficient infrastructure.

• Helped fast-growing AI and software companies reduce cloud infrastructure costs by 30–50% while maintaining performance and scalability;
• Designed and implemented cloud-native infrastructure, Kubernetes platforms, and CI/CD automation solutions;
• Led cloud migration, observability, security hardening, and platform modernization initiatives;
• Built scalable, cloud-agnostic platforms across AWS, GCP, and Azure to improve operational efficiency and engineering productivity;
• Advised clients on DevOps, FinOps, and infrastructure best practices to support sustainable growth and platform reliability.

An Internal Developer Platform built for a broadcast software provider serving global media organizations. Designed around Kubernetes and multi-cloud principles, the platform streamlined application deployment, monitoring, disaster recovery, and development workflows while ensuring high availability and operational consistency.

• Designed and built an Internal Developer Platform (IDP) on Kubernetes for enterprise-scale software delivery;
• Built 8 Kubernetes clusters in failover pairs to support automated testing and platform resilience;
• Improved development velocity by 30–50% by eliminating manual environment provisioning;
• Introduced Tekton-based CI/CD pipelines to standardise cloud-portable deployments;
• Implemented Terraform and Helm as golden-path infrastructure tooling across environments;
• Built multi-cloud failover architecture across AWS, GCP and on-prem datacentres;
• Developed Grafana observability dashboards for real-time broadcast channel health monitoring;
• Implemented backup, disaster recovery and point-in-time recovery strategies with zero data loss objectives;
• Produced operational runbooks, compliance documentation and DR training materials;
• Led platform reliability and business continuity planning initiatives.

An AI infrastructure platform supporting large language model inference and AI-powered chat services, built on scalable Kubernetes and GPU-accelerated cloud infrastructure.

• Designed and delivered a production-grade AWS EKS platform for LLM inference workloads;
• Reduced infrastructure costs by approximately 50%, saving around £180k annually;
• Implemented GPU sharing and time slicing using the NVIDIA Device Plugin;
• Built KEDA-based autoscaling using GPU utilisation and inference queue depth metrics;
• Designed secure Kubernetes networking with private worker nodes, VPN connectivity and DNS whitelisting;
• Created Terraform templates enabling fully reproducible DEV, UAT and PROD environments;
• Built Kafka and Zookeeper infrastructure for reliable inter-service communication;
• Worked directly with leadership on microservices platform architecture and migration planning;
• Improved platform reliability, observability and deployment consistency.

A quantitative data and analytics company specializing in automated data collection and real-time business intelligence platforms

• Led the design and implementation of a cloud-native infrastructure platform supporting high-volume data ingestion, distributed analytics workloads, and internal development operations;
• Built and scaled Kubernetes-based infrastructure across AWS and Azure;
• Introduced infrastructure-as-code and containerization standards to improve platform consistency, scalability, and operational efficiency;
• Implemented observability, messaging, and security tooling to enhance reliability, monitoring, and operational visibility;
• Led Security, MLOps, and DevOps strategy to streamline operations, improve engineering efficiency, and support secure business growth;
• Optimized CI/CD pipelines, reducing build times to under 7 minutes;
• Enabled self-service development capabilities for engineering teams, reducing cloud infrastructure costs by 40%;
• Collaborated with engineering and data science teams to build scalable, reliable platforms for data processing and machine learning workloads.

A quantitative data and analytics company specializing in automated data collection and real-time business intelligence platforms.

• Built infrastructure-as-code templates to enable scalable, automated, and repeatable cloud deployments;
• Containerized Python, Java, and C# microservices using Docker and Kubernetes;
• Led cloud migration initiatives from enterprise platforms (Microsoft, VMware, Nutanix) to cost-effective open-source and cloud-native solutions;
• Designed and maintained cloud infrastructure and deployment platforms to support business growth and operational scale;
• Led data science and engineering teams in developing reliable, scalable platforms for machine learning workloads and data processing;
• Implemented and optimized CI/CD pipelines to improve deployment consistency, platform reliability, and delivery speed;
• Enhanced scalability, performance, and resilience across internal and customer-facing systems.