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01/Expertise

Depth where delivery gets difficult.

Principal-level direction, hands-on engineering and stronger delivery systems for consequential product and platform work.

01 · Leadership

Principal engineering & technical leadership

For organisations that need senior technical direction without removing delivery responsibility from the role.

Lee turns broad outcomes into coherent technical direction, coordinates delivery across teams and keeps architectural decisions grounded in implementation reality.

  • Technical directionArchitecture, roadmaps and consequential design decisions.
  • Multi-team deliveryAlignment across products, services, repositories and disciplines.
  • Engineering standardsTesting, accessibility, security, operability and maintainability.
  • Hands-on contributionDirect implementation on difficult foundations and high-risk work.

See principal engineering in practice at BPP

02 · Platforms

Cloud platform & product delivery

For teams building or modernising business-critical digital products without losing control of reliability or delivery risk.

Current work centres on TypeScript systems and AWS infrastructure managed through Terraform, from user-facing applications through to events, data and operations.

  • Product architectureReact, Next.js and Node.js systems shaped around real user needs.
  • Cloud foundationsServerless and container workloads, infrastructure as code and delivery pipelines.
  • Resilient integrationAPIs, queues, events, transactional outbox patterns and failure recovery.
  • Operational readinessObservability, secure access, automated testing and supportable systems.

Tools chosen for the work

TypeScript, React/Next.js, AWS and Terraform underpin recent platform work. Astro and Cloudflare support focused, smaller-scale products.

  • Amazon Web Services
  • TypeScript
  • React
  • Next.js
  • Node.js
  • Terraform
  • PostgreSQL
  • Astro
  • Cloudflare

03 · Effectiveness

Engineering effectiveness & responsible AI

For engineering organisations that want practical gains from AI without compromising quality, governance or human judgement.

AI works best as part of a disciplined engineering system: useful context, bounded tasks, isolated delivery, automated checks, reviewable changes and explicit human decisions.

  • Operating modelsClear workflows for investigation, planning, implementation and review.
  • Portfolio automationRepeatable maintenance and operational work across service estates.
  • Tool integrationSource control, CI, work management and developer environments.
  • Human controlAuditable work with judgement retained at consequential boundaries.

Explore the approach in Kiri

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For contract or consultancy enquiries, contact Lee via LinkedIn. Share the product or platform challenge, the support your team needs and your likely timescale.

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