Selected engineering work

Engineering challenges shaped by leadership decisions and measured by outcomes.

A selection of complex engineering challenges I’ve led across platform modernisation, distributed systems, AI enablement, engineering effectiveness, security and organisational transformation.

These case studies focus on the problem, decisions, leadership and outcomes rather than proprietary implementation details.

Engineering Leadership · Architecture · AI · Platforms · Transformation

Explore the work ↓

Featured

Where the constraint was not obvious

I lead engineering organisations through complex technology problems—scaling platforms, modernising systems, improving engineering effectiveness and helping teams adopt AI safely and effectively.

AI Engineering

Building an AI-First Engineering Operating Model

AI development tools were being adopted across engineering teams, but usage stopped at the coding step and varied team to team — creating inconsistent quality, security, governance and repeatability, and no measurable engineering value to point at.

1× → 3×

Project execution and delivery speed

Averaged across participating teams, from inception and ideation through to rollout

My roleDesigned and introduced an AI-First approach across multiple engineering teams, covering the full delivery lifecycle — inception, ideation, design, build, verification and rollout — rather than treating AI as an autocomplete tool inside the coding step alone.

AI Engineering Developer Experience Engineering Productivity TDD DevSecOps

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Platform Modernisation

Modernising Legacy Technology Without Disrupting the Business

A mature technology estate contained legacy frameworks, applications and components that created increasing maintenance, security and engineering productivity risks.

Unsupported → Supported

Legacy platform estate

Modernised incrementally, with no big-bang rewrite

My roleLed and influenced modernisation strategy, architecture decisions, prioritisation and technical-risk management while ensuring business-critical capabilities continued operating throughout the transformation.

Modernisation Architecture Technical Debt Platform Engineering Risk Management

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Fintech & Blockchain

Accepting FIAT and Crypto, Issuing Share Contracts On-Chain

A private members' club needed to accept share purchases from its members in both traditional currency and crypto, and to give each member a verifiable record of what they owned — across two settlement models that have almost nothing in common.

FIAT + Crypto → On-chain

One share-purchase flow, five settlement assets

Every purchase produced its own Solidity contract on the Ethereum Virtual Machine

My rolePart of the team that built and maintained the platform end to end: payment acceptance across FIAT and crypto rails, the member share-purchase flow, and the generation and deployment of a Solidity smart contract for every purchase to the Ethereum Virtual Machine.

Fintech Blockchain Smart Contracts Solidity Ethereum

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Platform Engineering

Turning Integrations Into a Repeatable Engineering Capability

New external integrations traditionally required significant specialist engineering effort, creating scalability constraints and knowledge concentration around a small number of senior engineers.

Before → After

From specialist bottleneck to platform capability

Build the capability once. Enable teams to use it repeatedly.

My roleLed the engineering strategy for introducing reusable patterns, tooling and code-generation capabilities that reduced repetitive integration work and made implementation accessible to a broader range of engineers.

Platform Engineering Automation APIs Integration Architecture Developer Experience

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Engineering Leadership

Building a Measurable Engineering Operating Model

Engineering teams were delivering software, but inconsistent engineering practices made delivery predictability, technical health and continuous improvement difficult to measure.

DORA + system health

Measure the engineering system — not individuals

Metrics create conversations, not surveillance

My roleIntroduced and strengthened engineering practices designed to create predictable delivery, stronger quality and greater ownership while avoiding unnecessary process overhead.

Engineering Leadership DORA Engineering Effectiveness Developer Experience Continuous Improvement

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Enterprise SaaS

Leading Multi-Region SaaS Delivery

Deliver a significant platform capability across multiple production regions while maintaining service reliability and supporting users through early production adoption.

Multi-region

Production delivery across geographic regions

Leadership continues through rollout and stabilisation

My roleLed engineering delivery across planning, architecture discussions, release readiness, deployment coordination, production support and post-release stabilisation.

Enterprise SaaS Cloud Reliability Multi-Region Engineering Leadership

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Security Engineering

Moving Security Into the Engineering Workflow

Security controls are often introduced late in the development lifecycle, increasing remediation costs and creating friction between delivery and security teams.

Shift left

Make the secure path the easiest engineering path

Security as capability, not late-stage gatekeeping

My roleInfluenced and strengthened approaches that shift security controls earlier into engineering workflows so secure development becomes part of normal delivery.

DevSecOps Security Automation Engineering Governance Shift Left

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Scale

Engineering at scale

Signals of the environments and systems where this work happens — not a résumé scoreboard.

15+

Years software engineering

6+

Years engineering leadership

Multi-team

Engineering organisations

Multi-region

Enterprise platforms

2.5×+

Transaction throughput improvement

Enterprise SaaS

Complex distributed platforms

AWS + Azure

Cloud architecture

AI-First

Engineering enablement

Method

How I approach engineering challenges

The objective isn't simply to deliver more software. It's to continuously improve the organisation's ability to deliver valuable software.

  1. 01

    Understand the System

    Understand the business objectives, architecture, teams, dependencies, constraints and customer impact.

  2. 02

    Find the Constraint

    Identify what is genuinely preventing the engineering organisation or platform from moving forward.

  3. 03

    Design for Leverage

    Use architecture, platforms, automation, engineering practices or organisational change to remove that constraint.

  4. 04

    Deliver Incrementally

    Prefer measurable progress over transformation programmes that take months before producing value.

  5. 05

    Measure the Outcome

    Measure reliability, delivery performance, engineering health, quality, security and customer/business outcomes.

Capability

Technology I’ve worked across

Technology is a means of creating leverage—not the outcome itself.

Architecture

Distributed Systems · Microservices · Event-Driven Architecture · REST APIs · Multi-Tenant SaaS

Cloud

AWS · Microsoft Azure

Engineering

.NET · C# · PHP · Python · JavaScript · Node.js · React · Angular

Data & Messaging

MySQL · SQL · Kafka · Data Pipelines

Engineering Platforms

CI/CD · Containers · Observability · DevSecOps · Engineering Automation

AI

LLMs · Agentic Systems · RAG · AI Engineering Workflows · AI Governance · Engineering Agents

Working on a difficult engineering problem?

I’m interested in problems where technology creates leverage.

Whether the challenge is scaling an engineering organisation, modernising a platform, improving software delivery, introducing AI into engineering workflows or shaping technology strategy, I enjoy working at the intersection of technology, people and business outcomes.

Read my perspective on AI-first engineering