Principal Enterprise Architect & Engineering Technology Lead

Candidate Description

Driving enterprise AI adoption and platform engineering at scale, the candidate combines hands-on delivery with senior architecture leadership across banking, legal services and technology consulting. Their experience spans infrastructure engineering, site reliability, DevOps, cloud governance and production generative AI. At a financial institution, they lead engineering architecture affecting 11,000 engineers and a team rebuilding tools for approximately 400 architects. Their technical foundation includes Azure, AWS, Azure OpenAI, Python, TypeScript, PowerShell, Kubernetes and CI/CD. They bring particular strength in translating governance requirements and complex service-domain knowledge into practical engineering platforms and reusable delivery patterns.

Production delivery of agentic applications, model-routing platforms and retrieval-augmented generation systems distinguishes their technical capability. At a legal services firm, they delivered legal AI workflows adopted across every practice, with lease and privacy-policy reviews returning in approximately 10 minutes and saving an estimated 12.5 billable hours on a typical 50-page document. They customised LangChain for cyclical agentic workflows and used Azure API Management to integrate Amazon Bedrock and load-balance Azure OpenAI deployments, supporting more than 600 concurrent users. At a financial institution, they productionised Specwright and CGC, with CGC reducing manual architecture-review effort by approximately 30%. Their delivery approach combines SDLC architecture, infrastructure as code, automated GitHub approvals, secure release controls and assurance evidence aligned with regulated environments.

Their leadership combines strategic direction with mentoring, cross-functional collaboration and ownership from discovery through implementation. At a legal services firm, their three-engineer team achieved two promotions, a 37% reduction in critical-incident resolution time and a 60% increase in business-as-usual productivity. They also advise the Chief Data Officer at a financial institution on divisional AI adoption and have led standards adoption across more than 10,000 engineers. Consulting delivery at a technology consulting firm included work for a legal services firm, a water utility and a financial services firm, demonstrating adaptability across professional services, utilities and financial services. Their overall value lies in connecting enterprise architecture, AI engineering, operational reliability and governance to deliver platforms that are scalable, auditable and useful to the business.