NYC, US - 2024 - 2025
Working on Monarch, a planet-scale, in-memory time series database system primarily used for monitoring performance, availability, load, and other operational metrics of large-scale applications and infrastructure. Monarch is a multi-tenant service capable of ingesting terabytes of data per second, storing nearly a petabyte of time series data in memory, and handling millions of queries every second.
NYC & London, 2023 - 2024
Engineered an advanced recommendation platform to integrate seamlessly with sales workflows, aligning customer requirements with tailored cloud solutions. The platform leverages novel research to chain multiple large language model (LLM) agents, employing Generative AI to map customer needs to optimised cloud architectures, cost projections, and deployment strategies.
London, UK - 2022
Developed and open-sourced robust tools for in-depth website performance analysis and optimisation, empowering businesses to enhance user experience and operational efficiency. Provided consulting to major advertising clients, delivering tailored strategies to significantly improve website performance, maximise ROI, and competitiveness.
London, UK - 2017 - 2022
Played a key role in developing reporting automation platforms and led the strategic shift from legacy thick clients to advanced, feature-rich web applications. Managed a team of two engineers to enhance the data analytics platform utilised by the accounting team, driving improvements in efficiency, scalability, and functionality that directly supported data-driven decision-making across the organisation.
London, UK - 2015 - 2016
Graph theory and high-performance browser-based rendering techniques for visualising complex dependencies across thousands of heterogeneous, cross-system batch jobs executing daily processes. Developed both live and replayable visualisations to improve real-time observability and post-event analysis, significantly reducing operational toil associated with debugging and system monitoring. This solution enhanced system transparency, facilitating faster issue resolution and deeper insights into inter-process dependencies.
Work on JVM agents to accurately identify active class usage within a large-scale Java and Scala codebase running across thousands of production machines. Moving beyond artefact-level checks, these agents precisely tracked code utilisation in live environments, enabling targeted deprecation and facilitating the cleanup of a substantial percentage of redundant code. This initiative optimised the codebase, improving maintainability and performance across the system.
Manchester, UK - 2014 - 2018
Served as CTO, senior software engineer, and consultant for multiple startups, immersing in entrepreneurship across industries such as game development, sports, and data analytics. Led the development of multi-platform applications designed for scalability and reliability, deployed at scale on AWS to meet diverse user needs and operational demands.
2025 - present
Uphold the highest professional standards and help shape the future of technology.
2025 - present
2024 - present
Enabling volunteering across IEEE societies through enhancements of the volunteer.ieee.org platform.
2024 - present
Mentoring, supporting the elevation of senior members, and paper reviewing.
2025 - 2026
Joined the Trustee team for the SocRSE non-profit organisation (charity number: 1182455) to help support software engineering as a super-power for researchers.
2025 - present
2024 - 2025
Supported undergraduate students participate in a 10-week virtual experience to prepare for interviews and a career in software development.
2023 - present
Provided personal and career development support for Googlers around the world.
<> 1994 © 2025 </>