Laurie Hawkins
I build engineering organisations and platforms that make other engineers more effective.
Impact
The Journey
Tech wasn't Plan A.
Spent nearly a decade in healthcare as an Operating Department Practitioner. Decided to move into technology. Learned quickly. Found something I was good at.
Coming into engineering from outside the traditional route shapes how I lead today: focus on outcomes over tech-for-tech's-sake, comfort with unfamiliar territory, and interest in how technology enables people and business rather than just building systems.
What I Do
Selected Work
Scaling Platform Capability
2022–2026Single Platform Engineering team supporting 3 AWS accounts. Growing product portfolio and acquisition activity required expanded platform capability.
Designed and scaled leadership structure across 5 engineering functions. Developed technical leads. Established autonomous delivery model and clear ownership.
Now leading Platform Engineering, Core Services, Calculations, IT Support, and Professional Services across 50+ AWS accounts.
FinOps at Scale
2023–202450+ account AWS estate with limited cost visibility, no governance controls, and platform scaling without cost optimisation.
Established FinOps practices. Infrastructure modernisation. Kubernetes platform optimisation. Storage lifecycle management. Cost visibility improvements.
15–20% cost reduction while continuing to scale platform capability. Governance controls and visibility now standard practice.
Platform Resilience & Security
2023–2024DR capability exceeded 24 hours. 120+ critical vulnerabilities across platform. Regulatory requirements demanded improvement.
Platform modernisation programme. Dependency governance. CI/CD improvements. Infrastructure resilience work.
DR under 45 minutes. More than 120 critical vulnerabilities reduced. Platform now meets regulatory standards.
AI-First Development
2024–2026Engineers wanted AI coding tools. Existing local development posed risks: credential exposure, browser session leakage, source code access concerns.
Defined and led implementation of governed, model-agnostic AI development environments — isolated and air-gapped, with control over credentials, browser sessions and source code access.
AI coding tools safely adopted. Developer governance improved. Engineering productivity increased while maintaining security standards.
AI Cost Management
2025–2026AI usage spread across multiple services and tools with no attribution. Spend was growing without insight into which models were being used, by whom, or whether the cost was justified.
Led development of an AI cost visibility platform spanning Amazon Bedrock and Cursor, giving cross-model usage insight and attribution. Introduced spend guardrails and usage controls.
Teams manage consumption proactively. Engineers coached on model selection and cost–performance trade-offs, so higher-cost models get used where they genuinely add value.
Technology Ecosystem
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