A principal technologist with an extensive record of successfully solving business problems in start-ups, scale-ups, and enterprises across several regulated industries. Proficient at managing senior stakeholders and identifying workable solutions that fit the organisation. Helping fellow technologists grow in their career through coaching and/or mentoring leading to a more effective engineering community. Committed to continuous improvement through life-long learning.
Led a small team taking a modern search proof of concept into production to gather additional feedback from Lawyers across the globe. Tackling a core knowledge searchability problem within the organisation through modern AI powered search technologies. Repointed solutions to better align with the engineering function’s capability set. Advanced the use of automated testing within the Firm to maintain product quality and deliver regular product enhancements with confidence and without regression.
Developed communication-enabling solutions against an aggressive and immovable deadline in reaction to the Firm’s merger with Shearman and Sterling to form the third largest integrated global law firm A&O Shearman. Quickly acquired new skills and applying solid engineering fundamentals to successfully deliver a multi-tenant (Microsoft Entra and Exchange Online) communication and security enforcement solution. Worked with our Identity and M365 specialists to gain buy-in into the approach and gain governance sign-off.
Provided engineering and architectural oversight of an in-house developed application exposing LLM-backed assistance to Lawyers across the firm. Doubled the size of the team by leading the interviewing and successful recruitment leading to increased delivery throughput to meet the organisation's goals for the product. Worked with security professionals to maintain and enhance the security posture of the product.
Produced best practice designs covering fan-out operations within the durable task framework to allow for durable processing of ingested data in a fast and reliable manner utilising multiple workers. Operated effectively across both AWS and Azure cloud footprints. Migration of core usage tracking components from an AWS, Lambda, Node.js, DynamoDB stack to an Azure, C#, Durable Functions, Cosmos DB as part of a strategic realignment.
Developed an approach to analyse the historical usage trends of API and use that data to inform sensible rate limits. Rate limits became part of the documentation of the service and enforced by Azure API Gateway after deployment. Focussed on developer experience and reduced the amount of toil involved with the process.
Delivered talks to the team and Chief Technologists related to Domain Driven Design (including Context Mapping), along with a presentation on Explainable Artificial Intelligence during AVEVA’s Developer Conference in Cambridge.
Extending new quotation platform embedding an event sourced mechanism to cover persistence and high availability through clustering. Parachuted into a team building an MVP using Java and Neo4j. Performed an in-depth analysis of the solution and the health of the team. Guided the team to a deployment as a trial rollout serving Aviva France. Planned the next milestones and attached appropriate estimates to aid senior stakeholder decision making. C#, Akka.net, React, ASP.Net Core, Redis, PostgreSQL, Java 8, Neo4j, AWS Kinesis.
Green field environment to build a cloud native social network platform to allow content creators to connect with their supporters. Provided software engineering guidance and technical support for a successful R&D Tax Relief application
Performed as the technical authority aligned to the personal lines set of insurance products. Designed and lobbied for a new approach leverage reactive programming techniques through the actor programming model meeting the organisation’s strategic goals via question set rationalisation and consistency in approach. Led the team developing this quotation platform and aided in the upskilling and training into these new technologies. C#, Akka.net, React, SignalR, deployed into AWS.
Applying Domain Driven Design techniques to build a new gaming platform from the ground up. Responsible for the design and development of the Banking (including payment processing for deposit and withdrawal), Bonus, Promotion, and Customer Engagement bounded contexts. Working with a small team of developers in a green field environment to successfully deploy, and grow the website such that it attracted new investment based on a £100m valuation. C#, ASP.NET MVC, ASP.NET Web API, Entity Framework 4, Rabbit MQ, SQL Server.
Designing and leading development of a disruptive web based haulage planning system. Aided in the successful sale of the product into a number of established hauliers within the UK. Supported new deployments through training and on site "day-in-the-life" sessions. Led development of time-slot based activity sales software used by a well-known nationwide leisure company through a combination of online sales and back-office management portals. C#, ASP.NET Web Forms, ASMX, WCF, SQL Server.
Numerous multi-tier systems with VB6 COM+, XML with XSLT, and adopting .NET 1.0/1.1 C#.
MSc Computer Science with Artificial Intelligence
BSc Computer Science
Artificial Intelligence (AI) is being applied to an increasing number of facets of our lives. From scenarios such as recommendation engines through to complex systems designed to drive vehicles on public roads, there seems to be no end to the scope and variety of the tasks that AI techniques are being applied to. It is natural that these scenarios exist on a spectrum between what are referred to as low stakes towards those that would be described as high stakes. For example, a private individual may have less interest in YouTube’s recommendation engine providing appropriate and interesting content than they would be a system charged with detecting the presence of malignant cancers within tissue samples.
Machine Learning (ML) models can produce undesirable results or raise worrying questions. An individual’s life chances could be extremely negatively impacted by the misclassification of a tissue sample as benign instead of malignant. In instances where an individual has been harmed or exposed to potential harm it is reasonable for that individual and applicable regulatory bodies to ask the question as to why this happened such that suitable action can be taken. Developers of and researchers in AI systems may be able to build better systems and refine approaches if those systems have an ability to describe why model outputs have been determined. This need for explainability in systems has been known for many years, was acknowledged during the development of expert systems during the late 1970s and early 1980s, and within the field of AI is the focus of the sub-field of eXplainable Artificial Intelligence (XAI).
This research will attempt to determine the following: