Software Engineering • AI • Digital Systems
Software Engineer and AI Application Developer working across full-stack development, business systems, automation and production AI.
From architecture and development to integration, deployment and ongoing improvement.
KAMRAN CODE
ENGINEERING SYSTEM
Across the whole system
I work across the entire software lifecycle — understanding requirements, designing architecture, building applications, integrating AI and third-party systems, deploying production infrastructure and improving systems after launch.
01What I build
Six areas, one engineering approach: understand the problem, design the system, build it properly and keep it running.
02AI Engineering
Turning AI capabilities into useful software systems.
I build practical AI applications — systems where a model is one component inside a real product, wired to business data, tools and workflows — rather than adding a chatbot to a website and calling it AI.
Applications built around modern language models.
Knowledge bases, document search and semantic retrieval.
Tool calling, APIs, workflows and multi-step tasks.
AI-assisted business processes and repetitive workflow automation.
Extraction, classification, summarization and document question answering.
Semantic search and intelligent knowledge retrieval.
Reliable JSON outputs, classification, extraction and workflow integration.
Connecting models to business data, applications, APIs and internal systems.
How an AI system is layered
03Full stack
Frontend, backend, data and infrastructure handled by one engineer who understands how they fit together.
01/Frontend
02/Backend
03/Data
04/Infrastructure
04Business software
Most business problems are not solved by another marketing website. They are solved by systems built around real operational workflows — the way orders move, how customers are followed up, where data lives and who needs to see it.
Need a custom business system?Customer management, sales pipelines, follow-ups and reporting.
Content management, publishing workflows and administration.
Business operations, inventory, finance-related workflows and internal processes where appropriate.
Operational reporting and decision-support interfaces.
Custom software replacing spreadsheets and repetitive manual processes.
Secure interfaces for customers, students, staff, partners or other users.
Custom software connecting people, data and processes.
Selected projects
Case studies that walk through the problem, the architecture and what was actually built — with outcomes only where they can be stated factually.
Technology
A focused stack across TypeScript, React, Next.js, Laravel, PHP, relational and vector data, AI tooling and containerised infrastructure.
Experience
Working with a UK-based software team while also building software independently for businesses and product teams.
Employment
Present
XLEducation · United Kingdom
Independent
Ongoing
Kamran Code · Remote · UK & international
Engineering approach
I don't just write code. I engineer systems.
01
Understand the business, users and problem.
Who uses the system, what they need to do, what the current process looks like and what actually has to change.
02
Design the technical architecture.
Data model, boundaries, integrations, where AI genuinely helps and where it doesn't — decided before code is written.
03
Develop the product.
Backend, frontend and data layers built incrementally, with working software reviewed early rather than a big reveal at the end.
04
Connect APIs, AI and external systems.
Payment providers, email, CRMs, model providers and internal services connected with clear contracts and error handling.
05
Move the system into production.
Containers, CI/CD, environments, backups and monitoring so the system is operable — not just running.
06
Monitor, optimize and evolve the system.
Usage, performance and errors observed after launch and fed back into the next iteration.
Writing
Long-form, practical articles on AI engineering, architecture, business systems and the stack I work with.
You do not need a rewrite to add AI to a Laravel or Next.js application. A step-by-step approach: find the right feature, isolate the model behind a service, validate outputs, handle cost and failure, and ship behind a flag.
Tenancy, billing, background work, environments and the boundaries that let a SaaS product grow without a rewrite. A practical architecture for a first version that is built to last, with Next.js, Laravel and PostgreSQL as the reference stack.
When a generic CRM stops fitting, a custom one is often smaller than people expect. The data model, pipeline design, integrations and reporting that make a custom CRM worth building — and the signs that you should not.
Tell me what you're trying to build. I'll come back with an honest view on scope, architecture and the right approach.