AI Technical Lead & Senior Software Engineer

I build AI systems that work in production.

I lead and build commercial AI systems, from agentic data platforms and RAG to real-time conversational software. Underneath that is sixteen years of architecture, full-stack delivery, security, performance, and platform engineering.

Chris Clayton, AI Technical Lead and Senior Software Engineer
Open to permanent, remote-first roles with UK companies.
3 yearsCommercial AI delivery

Agentic platforms, RAG, computer vision, and real-time voice systems taken from R&D into production.

16 yearsProfessional software engineering

Web, APIs, desktop, data, integration, and infrastructure across complete product lifecycles.

Lead + hands-onArchitecture to production

Technical direction, mentoring, and detailed implementation without stepping away from the code.

Cloud + on-premEnterprise deployment

Systems designed for Azure, Kubernetes, and customer networks with real security and operational constraints.

Selected work

See all my work
Commercial AI

DataQI: enterprise agentic data platform

2023–present

DataQI lets organisations use an AI agent across documents, databases, and connected tools, with a choice of cloud-hosted or fully on-premises deployment.

Senior Engineer — Technical Lead for DataQI

  • C#
  • .NET
  • Python
  • React
  • RAG
  • Semantic Kernel
  • MCP
  • OAuth 2.0
  • Microsoft SQL Server
  • PostgreSQL
  • MySQL
  • SharePoint
  • Google Drive
  • Vector search
  • Kubernetes
  • Azure Kubernetes Service
Commercial AI

Applied AI R&D

Feb 2023–present

Turning open questions into working systems across computer vision, live video analysis, predictive modelling, IoT data, OCR, and the early foundations of enterprise RAG.

Senior Engineer — Lead Developer in Razor's AI team

  • Python
  • TensorFlow
  • LangChain
  • Semantic Kernel
  • RAG
  • Computer vision
  • Image classification
  • Video analysis
  • OCR
  • Predictive modelling
  • IoT
Commercial AI

Streaming conversational AI

2023–2024

A real-time phone system that streamed speech recognition, LLM orchestration, and speech synthesis while handling pauses, interruptions, and structured information gathering.

Senior Engineer — Technical Lead

  • C#
  • .NET
  • Python
  • LangChain
  • Semantic Kernel
  • Twilio
  • WebSockets
  • Azure Speech
  • Speech-to-text
  • Text-to-speech
  • Async/await
Commercial engineering at scale

SGBD Apps: security built into the platform

2018–2021

A modular ASP.NET Core platform that made secure access, auditability, and compliance the default route for replacing a large legacy application estate.

Senior Software Engineer — platform architect and lead developer

  • C#
  • ASP.NET Core
  • Razor
  • IdentityServer
  • OpenID Connect
  • SQL Server
  • Apache Solr
  • JavaScript
  • Knockout.js
  • Serilog
  • NuGet
  • TeamCity
  • Octopus Deploy
Commercial engineering at scale

SignOnGlass: distributed order display and signing

2017–2021

A real-time order display and signature platform deployed across more than 5,000 locations and over ten Saint-Gobain brands.

Senior Software Engineer — Technical Lead

  • C#
  • .NET Framework
  • ASP.NET MVC
  • SignalR
  • Knockout.js
  • SQL Server
  • WinForms
  • Win32
  • REST APIs
  • Wacom tablets
  • F5 load balancing
  • Windows Server
  • Group Policy
Commercial engineering at scale

Enable 2.0: learning at scale

2013–2016

A greenfield learning platform combining ambitious browser-based authoring, standards-based course delivery, PDF generation, and independently designed distributed load testing.

Software Developer → Architecture Owner

  • C#
  • JavaScript
  • Microsoft SQL Server
  • Entity Framework
  • T-SQL
  • ASP.NET MVC
  • .NET Framework
  • Knockout.js
  • SCORM 1.2
  • PDFsharp
  • MigraDoc
  • SignalR
  • WinForms
Public and inspectable work

HypnoTech

2020–present

A strongly typed modular CMS and application engine, manually built during furlough and later transformed through an inspectable Codex-assisted engineering programme.

Creator and lead developer

  • C#
  • .NET 10
  • Codex-assisted delivery
  • ASP.NET Core
  • JavaScript
  • MongoDB
  • Entity Framework Core
  • PostgreSQL
  • Microsoft SQL Server
  • xUnit
  • Playwright
  • Testcontainers
  • GitHub Actions
  • Podman
Public and inspectable work

Synth of Doom

2017–present

A playable polyphonic browser synthesiser, rebuilt from a preserved 2017 Angular/Web Audio project into a typed, accessible React application through a Codex-assisted modernisation.

Creator and developer

  • React
  • TypeScript
  • Web Audio API
  • Web MIDI API
  • Audio DSP
  • Vite
  • Vitest
  • Playwright
  • axe-core
  • SCSS
  • GitHub Actions
Public and inspectable work

WavLab: audio DSP in C++ and Rust

2022–present

Paired C++20 and Rust libraries and command-line tools that turn degree-era audio programming into tested, cross-platform systems work.

Creator and developer

  • C++20
  • Rust
  • Digital signal processing
  • PCM WAV / BWF
  • Binary file formats
  • CMake
  • Cargo
  • CTest
  • GitHub Actions
  • AddressSanitizer
  • UndefinedBehaviorSanitizer
  • CLI11
  • Clap
Public and inspectable work

GTK on Linux: learning by building

2026–present

A practical progression from a Python Flatpak utility, through C and GTK internals, to a security-conscious Rust application designed for the Xfce desktop.

Creator and developer

  • GTK 3 / GTK 4
  • Rust
  • C17
  • Python
  • Fedora Linux
  • Xfce
  • Flatpak
  • Libadwaita
  • Meson / Ninja
  • JSON-GLib
  • libsoup
  • D-Bus
  • AccountsService
  • Polkit
  • gettext
  • V4L2

Production AI

How I take AI systems from an idea into production.

I’ve taken AI products from early proof of concept through technical design, production deployment, and ongoing development. That includes retrieval and orchestration across documents, databases, and external tools, alongside applied computer vision, OCR, prediction, and voice systems.

The wider engineering work matters just as much: secure modular platforms, high-volume distributed systems, difficult performance problems, cloud and on-premises delivery, and software that remains maintainable after the demo. I have strong technology preferences, but I choose tools for the system in front of me and actively enjoy work that demands a new language or platform.

AI-assisted development is part of how I work, but it is not a substitute for judgement. I use it inside a disciplined process of specification, review, testing, and verification.

01

Agentic data platforms

Orchestration, tool routing, guardrails, and interfaces that help people work across complex enterprise information.

02

Retrieval across documents and data

Document, database, file-store, and MCP connections designed around scale, relevance, security, and deployment constraints.

03

Computer vision, prediction, and voice

Conversational voice systems, computer vision, OCR, classification, detection, prediction, and practical R&D.

Engineering foundation

The engineering experience I bring to AI work.

See my full technology list

Architecture and leadership

Technical direction, system design, mentoring, and clear ownership from the first proof of concept through production support.

Choosing the right tools

C# and .NET are my first choice for long-lived web and REST API platforms; I also deliver in Python, TypeScript and JavaScript, Java and Spring, C++, C, and Rust. Database work spans SQL Server, PostgreSQL, MySQL, MongoDB, and SQLite.

Security, scale, and performance

Secure modular platforms, distributed systems, observability, load engineering, cloud services, containers, and on-premises estates.

AI-assisted delivery

How I use AI while keeping responsibility for the result.

At Razor, I have been part of a substantial, practitioner-led AI transformation in how software is delivered. A high-trust culture let engineers choose effective tools, experiment, share what worked, and make AI-assisted engineering part of normal delivery. I use it across specification, implementation, automated testing, local code review, independent pull-request review, repository-wide analysis, and maintenance.

The quality gain matters as much as speed. Cheap, repeatable inspection makes it practical to test far more of an application and have separate agents challenge the same change from different directions. In recent work, that has meant broad test coverage and very few defects subsequently raised by QA.

  1. 01

    Frame

    Turn an ambiguous problem into explicit constraints, decisions, and an inspectable specification.

  2. 02

    Build

    Use the right mix of hands-on engineering and AI assistance to move quickly without surrendering control.

  3. 03

    Challenge

    Use local review, independent pull-request review, and repository-wide scans to challenge architecture, implementation, and assumptions.

  4. 04

    Verify

    Generate and run tests across application layers, inspect behaviour, and treat generated code as work to own rather than output to trust.

See how I used this on HypnoTech

Experience

My professional experience since 2010.

Read my full CV
  1. Jan 2022–presentRazor

    Senior Engineer — Technical Lead for AI products

    Led technical design and hands-on delivery across commercial agentic AI products and applied AI research, while supporting engineers and delivering customer systems.

  2. Apr 2017–Dec 2021Saint-Gobain Building Distribution

    Senior Software Engineer / Team Leader

    Built distributed in-store software and a security-led .NET platform for replacing a large estate of legacy business applications.

  3. Dec 2016–Apr 2017Silkwood Valley

    Senior Developer / Architect

    Architected and delivered cloud-connected ASP.NET Core and React applications across the Azure platform.

  4. Apr 2013–Oct 2016Virtual College

    Architecture Owner / Software Developer

    Progressed into architecture ownership while modernising and performance-engineering high-traffic learning platforms.

  5. Sep 2010–Apr 2013Egton Medical Information Systems

    Test Environments Engineer / Technical Tester

    Built deployment and approval tooling while managing complex test environments for healthcare software.

Beyond work

Music and audio have shaped how I think about software.

I studied Music Technology and Audio Systems, have recorded and released music for more than 25 years, and still build audio software in C++, Rust, React, and the browser. That work keeps engineering tangible: timing, signal flow, performance, and interface decisions are immediately audible.

See Synth of Doom

Contact

If my experience sounds useful to your team, get in touch.

I’m interested in permanent, remote-first roles with UK companies.

Huddersfield, West Yorkshire · open to suitable hybrid roles around Huddersfield, Leeds, and Bradford.

Email me