Azure & AI,
delivered simply.

Everyone can demo an AI prototype. Very few can hand one to a regulated pharma business and say “run this.” I built the platform the product stands on, the whole Azure estate defined as code in Bicep, Front Door and a WAF, API Management and Entra ID end to end, with managed identities so there’s not a single password or connection string stored anywhere. It’s a genuinely clever piece of AI, my job was to make it boring to operate, and that’s the part that decides whether it survives contact with the enterprise.

At iNova, we solve critical business challenges across integration, automation, data transformation, and regulatory compliance by applying Azure and enterprise data exchange technologies. … Through this combination of problem-solving and cloud technology, we help iNova improve operational efficiency, data accuracy, automation, compliance, and scalability across its IT landscape.

I bring extensive experience in software testing and Agile methodologies, enabling me to improve testing practices and streamline Agile processes that enhance the overall quality of applications. … By combining strong testing knowledge with Agile principles, I help teams deliver customer-focused solutions faster while maintaining high standards of quality, reducing risks, and ensuring applications meet both business objectives and user expectations.

I am bringing a modern, digital-first approach to operational planning by replacing fragmented Excel-based processes with a centralized solution built on Microsoft Power Platform. … This solution reduces manual effort, minimizes errors, improves visibility across departments, and provides a scalable platform that can adapt to future operational requirements.

I enjoy Data Engineering with expertise in Azure analytics, SQL, and Power BI, transforming complex raw data into clear insights and visualisations to streamline student journeys from admissions to progression and enhance financial management in the education sector.

I support enterprise integration, data transformation, and AI-powered knowledge solutions using Azure Data Factory (ADF), Azure Integration Services, and Azure AI Foundry. I ensure reliable data movement between SAP, Snowflake, Azure Storage and other enterprise systems by resolving production issues, optimizing pipelines, and improving automation and monitoring. I’ve also contributed to Azure AI Search and RAG implementations, building knowledge bases and integrating AI services with enterprise applications to deliver secure, scalable, resilient solutions.

We designed a multi-agent AI testing framework, specialised agents, a judge agent, and human-in-the-loop review, to validate the model’s logic. The workflow was orchestrated through structured AI prompting rather than custom code, achieving high-quality validation without building a dedicated testing platform. A fully manual approach was impractical, as each test could require reviewing hundreds of pages of documentation, while a coded solution would have increased project cost and consumed engineering capacity. It struck the right balance between quality, speed, and cost, enabling thorough testing while reserving human review for the ambiguous, high-judgement cases.

Everyone can demo an AI prototype. Very few can hand one to a regulated pharma business and say “run this.” I built the platform the product stands on, the whole Azure estate defined as code in Bicep, Front Door and a WAF, API Management and Entra ID end to end, with managed identities so there’s not a single password or connection string stored anywhere. It’s a genuinely clever piece of AI, my job was to make it boring to operate, and that’s the part that decides whether it survives contact with the enterprise.

At iNova, we solve critical business challenges across integration, automation, data transformation, and regulatory compliance by applying Azure and enterprise data exchange technologies. … Through this combination of problem-solving and cloud technology, we help iNova improve operational efficiency, data accuracy, automation, compliance, and scalability across its IT landscape.

I bring extensive experience in software testing and Agile methodologies, enabling me to improve testing practices and streamline Agile processes that enhance the overall quality of applications. … By combining strong testing knowledge with Agile principles, I help teams deliver customer-focused solutions faster while maintaining high standards of quality, reducing risks, and ensuring applications meet both business objectives and user expectations.

I am bringing a modern, digital-first approach to operational planning by replacing fragmented Excel-based processes with a centralized solution built on Microsoft Power Platform. … This solution reduces manual effort, minimizes errors, improves visibility across departments, and provides a scalable platform that can adapt to future operational requirements.

I enjoy Data Engineering with expertise in Azure analytics, SQL, and Power BI, transforming complex raw data into clear insights and visualisations to streamline student journeys from admissions to progression and enhance financial management in the education sector.

I support enterprise integration, data transformation, and AI-powered knowledge solutions using Azure Data Factory (ADF), Azure Integration Services, and Azure AI Foundry. I ensure reliable data movement between SAP, Snowflake, Azure Storage and other enterprise systems by resolving production issues, optimizing pipelines, and improving automation and monitoring. I’ve also contributed to Azure AI Search and RAG implementations, building knowledge bases and integrating AI services with enterprise applications to deliver secure, scalable, resilient solutions.

We designed a multi-agent AI testing framework, specialised agents, a judge agent, and human-in-the-loop review, to validate the model’s logic. The workflow was orchestrated through structured AI prompting rather than custom code, achieving high-quality validation without building a dedicated testing platform. A fully manual approach was impractical, as each test could require reviewing hundreds of pages of documentation, while a coded solution would have increased project cost and consumed engineering capacity. It struck the right balance between quality, speed, and cost, enabling thorough testing while reserving human review for the ambiguous, high-judgement cases.