CTO Cover Letter

I’m applying for the CTO role because I combine technical depth with leadership that turns architecture into predictable delivery. In my most recent role, I led 25 engineers across five squads, establishing technical leadership through structured ownership and decision-making.

I use AWS platform patterns with infrastructure as code in Terraform, alongside Kubernetes for scalable deployment, to reduce operational risk during release cycles. The result was a move to 30 deployments per day while maintaining 99.9% uptime through SLOs, automated rollback, and incident runbooks.

Strong engineering outcomes don’t come from better code alone—they come from an operating model that makes trade-offs visible. I’ve built team structures that separate product delivery from platform enablement, commonly through squads and tech lead governance that runs on clear engineering principles.

For example, I introduced engineering standards for code review, branching strategy, and release hygiene using tools like GitHub and Jira for traceability and reporting. I also implemented a sustainable on-call and incident process with post-incident reviews, using metrics such as MTTR and error budget burn rate to prioritise what mattered.

As CTO, I focus on architecture that scales safely and improves time-to-market without increasing operational chaos. In practice, that means designing for resiliency with circuit breakers, idempotency, and observability built in from day one, rather than added after incidents.

I’ve deployed microservices on AWS and managed delivery via CI/CD pipelines using GitHub Actions, with Datadog dashboards to monitor latency, saturation, and error rates. On one programme, these measures supported availability rising from 99.5% to 99.9% while reducing the backlog created by production issues and expensive manual troubleshooting.

CTO work is inherently cross-functional: engineering choices must be legible to Product, Finance, and the wider leadership team. I’ve owned parts of an annual £2M IT budget, translating platform investments into expected outcomes such as reduced downtime, faster feature throughput, and lower incident costs.

I partner with Product to use data-backed prioritisation—balancing reliability work with roadmap items—supported by backlog visibility in Jira and outcome tracking via KPI reporting. Where needed, I bring governance to architecture reviews so we can move quickly while keeping security and compliance obligations on track, including secure-by-default practices and access control.

If selected, I would start by diagnosing the current delivery and reliability system: deployment pipelines, on-call patterns, SLOs, and where quality gates are slowing teams down. In the first 30 days I typically run a focused assessment of infrastructure and operational maturity—reviewing CI/CD reliability, Kubernetes/runtime health, and observability coverage using tools like Datadog.

In parallel, I hold structured sessions with tech leads and product stakeholders to confirm constraints, clarify ownership, and define decision paths for architectural changes. By days 60–90, I’d present a short technical strategy with measurable targets for uptime, deployment frequency, MTTR, and technical debt reduction, alongside a plan for enabling squads to deliver safely.