AWS & Azure Cloud and Data Architect
9+ years · Agentic AI Engineering
I’m a forward deployed engineer and AI implementation lead, and I design and build cloud platforms that other teams and agents can rely on.
I use agentic AI in day-to-day delivery: multi-agent spec-writing playbooks for data-pipeline, web and infrastructure work, with adversarial verification and an ADR loop; harness and context engineering; and agent-runnable tooling for Azure DevOps backlog sync and workspace setup. My knowledge base on AI engineering covers six disciplines: Prompt Craft, Context, Harness, Intent, Specification and Orchestration Engineering.
Claude Code
Over eight years I’ve moved from .NET web applications and microservice migrations on Azure to leading AWS cloud and data architecture. My recent work includes CI/CD and reusable infrastructure modules, platform standards for APIs and caching, GDPR compliance, and an analytical data product on the medallion architecture.
I'm an AWS & Azure Cloud and Data Architect based in Leeds, United Kingdom, and today an Agentic AI Implementation engineer, Forward deploying AI solutions to business.
I design and build cloud platforms that other teams and agents can rely on. Over eight years I've moved from .NET web applications and microservice migrations on Azure to leading AWS cloud and data architecture. My recent work includes CI/CD and reusable infrastructure modules, platform standards for APIs and caching, GDPR compliance, and an analytical data product on the medallion architecture. I also use agentic AI in day-to-day delivery: multi-agent spec-writing playbooks for data-pipeline, web and infrastructure work, with adversarial verification and an ADR loop; harness and context engineering; agent-runnable tooling for Azure DevOps backlog sync and workspace setup; and a structured knowledge base on AI engineering disciplines.
Good architecture is mostly invisible. It's what lets everything else move fast and keep working under load.
From cloud and data architecture to the platforms and web apps on top, I work across the whole stack. I design systems, then build, ship and run them.
I design well-architected systems on AWS, Azure or anywhere, turning requirements into resilient, scalable and cost-aware solutions.
Multi-agent spec-writing playbooks with adversarial verification and an ADR loop, built on harness and context engineering.
Data modelling, pipelines and analytics, through to operationalising machine learning from features to production.
Infrastructure as code, CI/CD and Kubernetes, and the .NET APIs and web apps on top. I ship and run platforms, not just build them.
MSc Advanced Computer Science (Cloud Computing)
2022 – 2023
B.Tech in Computer Science Engineering
2012 – 2016
9+ years of professional experience across 4 roles
Leading AWS cloud solutions, data architecture and agentic development.
Architected and built microservice-based platforms on Azure, with the data pipelines and stores behind them, and owned their delivery to cloud infrastructure through infrastructure-as-code and CI/CD.
Modernised legacy monoliths into cloud-hosted microservices on .NET Core, designing APIs, data models and integrations, building analytics and reporting features, and mentoring developers across the team.
Built ASP.NET web forms and MVC applications, and contributed to proof-of-concept work across data access, services and early analytics.
A decade of delivery and research, from architecting Azure platforms to modernising decade-old monoliths and prototyping with AI. Each card opens into the context, my contribution and the outcome.
Built agent tools and workflows that carry the platform's infrastructure and deployment rules from specification to tested code.
Architected an analytical data product on the medallion architecture, built entirely from AWS services.
Built the framework for web applications on AWS, from API Gateway and Lambda or ECS to SQS, IAM, SSM and Secrets Manager, and built APIs on it.
Led the CI/CD for AWS cloud-native development and the plug-and-play infrastructure modules it deploys.
Built agent tools and workflows that carry the platform's infrastructure and deployment rules from specification to tested code.
Architected an analytical data product on the medallion architecture, built entirely from AWS services.
Built the framework for web applications on AWS, from API Gateway and Lambda or ECS to SQS, IAM, SSM and Secrets Manager, and built APIs on it.
Led the CI/CD for AWS cloud-native development and the plug-and-play infrastructure modules it deploys.
Built a long-running GDPR retention job on ECS Fargate that removes personal data once it is no longer needed.
Introduced Valkey as a shared distributed cache and one standard caching approach across the application.
Built an event-driven compliance job on AWS Lambda and EventBridge so the company's compliance checks always run.
Built a centralised document-generation platform on Azure, validating policy data with InRule across products.
Remapped a legacy system into modern APIs and mentored the team through the transition.
Migrated a monolith to microservices on AKS with dynamic, reflection-driven reporting.
Architected an Angular + GraphQL skills-search platform for managers, deployed on AKS.
Stood up a buffer microservice that kept forms and documents flowing correctly across systems.
Worked on modernising AS400 and in-house legacy systems into a microservice architecture for quoting, payment, policy and renewals.
Led the modernisation of a decade-old, 42-project WebForms application into microservices.
Enabled seamless, secure single sign-on transfer between a .NET and a Java platform.
Refactored a reimbursement monolith into microservices with stateful, automated email workflows.
Built the Angular UI skeleton and helped shape the GraphQL backend over a normalised schema.
Prototyped across a broad stack and built custom UiPath activities for ImageRight automation.
Built a multi-tenant PostgreSQL platform where one EF Core migration set provisions every tenant, across all three isolation strategies.
Authored a .NET library that evolves domain models over time while keeping full backward compatibility with older stored data.
Authored a .NET library that intercepts deletions and stores immutable archive snapshots with TTL policies and cascade archiving.
Built a reusable Terraform sample library covering the Azure estate, consumed by hundreds of pipeline-driven deployments.
Prototyped an access-review tool that surfaces the data reviewers need to decide.
Built a smart PDF-form prototype that prefills from prior data and generates completed forms.
Prototyped a sign-language interpreter using Custom Vision and text-to-speech.
Whenever you want to achieve something, keep your eyes open, concentrate and make sure you know exactly what it is you want. To accomplish great things we must not only act, but also dream, not only plan, but also believe.
Machine learning in production
October 2026Operationalising machine learning on AWS: preparing data and engineering features; building, training, tuning, deploying and monitoring models in production; and applying MLOps, automation, model governance, security and cost control, centred on Amazon SageMaker.
Data pipelines & analytics
June 2026Building and operating data pipelines on AWS: ingesting, transforming and orchestrating batch and streaming data; designing and managing data stores; cataloguing, governance and security; and optimising data for analytics with services such as Glue, Kinesis, Redshift, Athena and Lake Formation.
Well-Architected solution design
February 2026Designing and deploying well-architected solutions on AWS: resilient, high-performing, secure and cost-optimised architectures across compute, storage, networking and databases, applying the AWS Well-Architected Framework to turn business requirements into systems that scale.
Azure Solutions Architect Expert
July 2021Expertise crafting cloud and hybrid solutions on Azure across Compute, Network, Storage, Monitoring and Security, advising stakeholders and translating business requirements into solutions aligned with the Azure Well-Architected Framework, then implementing them alongside Developers, Administrators, Security and Data Engineers.
DevOps Engineer Expert
February 2022Bridging development and operations to enable continuous delivery: collaboration, code management, infrastructure provisioning, source control, security, compliance, CI, testing, delivery, monitoring and feedback, with a strong focus on Terraform, Azure DevOps and GitHub.
Azure Developer Associate
May 2021Responsible across all stages of development (requirements, design, deployment, security, maintenance, performance tuning and monitoring), spanning SDKs, storage, data connections, APIs, app auth, container deployment and debugging.
Web Applications
September 2017Professional developer using Visual Studio and ASP.NET (incl. .NET Core) to architect web solutions: designing and developing ASP.NET MVC applications, planning user-interaction solutions and deploying to multi-tier environments including Azure.
Programming in C#
CertifiedWriting applications in C#: managing program flow, events and asynchronous processing; creating and using types, encapsulation and inheritance; debugging, validating input, encryption and diagnostics; and implementing data access with collections, LINQ, files, serialization and databases.
Querying Data with Transact-SQL
January 2018Managing data with Transact-SQL: SELECT queries, joins, functions and aggregation, data modification, subqueries, APPLY, table expressions, pivoting, temporal and non-relational data, plus stored procedures, functions, triggers, views, error handling and transactions.
Software Development Fundamentals
December 2016Core programming principles: storage and data types, decision structures, repetition and error handling; object-oriented concepts; application life cycle; algorithms and data structures; web, desktop and database application fundamentals.
Building production applications with Claude
In preparationArchitecting production applications on Claude: where the model fits in a system and what it can and cannot do, prompt and context design, reliable integration through the Claude API, evaluation, and the guardrails that make a deployment safe to run.
Enterprise-scale Claude deployments
In preparationDesigning and leading enterprise-scale Claude deployments: solution and integration architecture, context engineering, evaluation and optimisation at scale, and AI governance, risk management and responsible deployment practices across stakeholders.
Notes on cloud & data architecture, .NET engineering and the practice of shipping software.
A chat window bolted onto a product is not an AI strategy, and neither is an assistant licence mandated for developers - the case for adoption with intent, and the staged-maturity evidence behind it.
The diagnosis came back genuine and the repository is empty - now the discipline the old system used to impose for free must be rebuilt by hand. Greenfield delivery as three questions (decide, prove, ship) and the gates an AI-assisted team still owes itself.
Teams ask for a rewrite as though greenfield were a reward for enduring the old codebase - it is a diagnosis with a test attached, and misdiagnosis is how rewrites fail. Part 1 of 2 on choosing the field you build on.
