About
I build software where mistakes become visible: manifesting as fleet-wide service outages, incorrect bookings, slow and expensive test suites, or eroded trust. My experience spans hyper-scale cloud systems, machine learning, embedded software, and aerospace. The common thread is not a single tech stack, but systems where mistakes outlive the deployment that caused them.
I thrive on novel or complex problems that require deep research, thoughtful design, and consensus before implementation. My strength lies in turning an ambiguous problem into a documented plan, and then into a resilient system a team can build, maintain, and expand for years.
Leadership
People are the most influential force behind any software project. An excellent engineer working alone has an upper limit on their output and natural blind spots in their knowledge. A good team, working together, will always build something better than an excellent individual could alone.
Many software challenges stem from human factors: missing information, unspoken assumptions, or misunderstood trade-offs. I lead by making knowledge seamless to share. In practice, that means writing clear designs, documenting decisions, building consensus early, and always assuming my peers know something I don’t.
Technical Direction
The initial implementation is rarely the full cost of software. The real expense includes long-term maintenance, debugging, and feature expansion. While velocity matters, it often presents a false economy. Time invested upfront with stakeholders, researching the problem, and refining designs is repaid continuously in bugs that never happen, design dead-ends that are avoided, and new capabilities added seamlessly.
Not every system needs to be perfect. Engineering is a discipline of trade-offs, and good judgement lies in knowing which compromises to make. I build with an eye towards software that is well-documented, thoroughly tested, and free of needless complexity.
Selected Impact
I’ve worked across systems with diverse failure modes: leaked sensitive information, sluggish user experiences, expensive test-feedback loops, customer booking errors, or lost telemetry from physical systems. The mindset required is often similar: understand the risks, isolate the causes, and leave the system better than I found it.
This approach has led to worldwide bootloader updates for a major cloud provider, machine learning systems that reconcile ambiguous supplier data, test framework improvements saving thousands of hours a year, and deployment pipelines that deliver startups’ first builds reliably.
Consulting
I am always open to consulting and advisory opportunities, though my availability is sometimes limited. I bring the most value to teams facing complex technical challenges without a clear next step: whether that means scaling a system, reviewing critical designs, or diagnosing reliability issues. I partner with organisations as either an advisor or hands-on engineer, specialising in system design, performance optimisation, reliability engineering, and deployment practices.