Work with me
I'm an enterprise software engineer and Generative AI solutions architect with 15+ years building secure, scalable platforms. I take on a small number of engagements at a time — architecture consulting, hands-on delivery, or an ongoing advisory role — for teams who need the system right, not just shipped.
Every engagement starts the same way: understand the business outcome, design deliberately, and leave your team able to keep evolving what we build.
Ways of working together
Discovery sprint
A short, fixed-scope engagement to map the domain, surface the risks, and produce an architecture and delivery plan you can act on.
- Domain and system modelling with your team
- Risk, cost and build-vs-buy assessment
- A written architecture decision record and phased delivery plan
Best for: Teams about to start — or restart — a significant build and wanting the shape right first.
Project delivery
End-to-end build of a product or platform feature, from schema to production, with a small senior team and a working slice every week.
- Architecture, implementation and deployment owned end to end
- CI/CD, observability and documentation shipped with the code
- Handover that leaves your team able to keep going
Best for: Founders and product teams who need a dependable system built, not just advice about one.
Fractional architect / advisory
Ongoing architecture and technical direction alongside your team — design reviews, key decisions, and unblocking, a few days a month.
- Regular architecture and code reviews
- Technical decision-making and trade-off analysis
- Hiring input, roadmap pressure-testing and incident retrospectives
Best for: Scaling teams that need principal-level architecture judgement without a full-time hire.
AI adoption consulting
Finding where generative and agentic AI actually earns its place in your product, and building the first version that holds up in production.
- Use-case discovery and feasibility assessment
- RAG, agent and evaluation architecture
- A working first implementation with guardrails and metrics
Best for: Product teams under pressure to "add AI" who want it done where it pays off, not everywhere.
Not sure which fits? Tell me about your projectand I'll suggest a shape.
Development Process
Every successful product begins with a clear vision and reaches its full potential through a disciplined engineering process. I combine strategic planning, modern software architecture, AI-driven innovation, rigorous quality assurance, and cloud-native DevOps practices to deliver scalable, secure, and production-ready solutions. From initial discovery and system design to deployment and continuous improvement, every stage is focused on building software that is reliable, maintainable, and designed for long-term business growth.
1. Discovery & Planning
2. UI/UX & System Design
3. Development
4. Quality Engineering
5. Deployment & DevOps
6. Support & Continuous Improvement
Selected delivery work
AegiSense — Multi-Tenant Identity & Authorization Platform
A self-hosted, multi-tenant Identity & Access Management platform that unifies authentication, RBAC/ABAC/ReBAC authorization, SSO and federation, user lifecycle and identity governance behind a single policy engine — for regulated, on-premise and high-scale environments.
Read case study
Employee Background Verification Platform
Sole engineer on a production, multi-tenant background-verification SaaS — ~105,000 hand-written lines across two repositories. It runs the full lifecycle of employee and business checks, 14 verification types per subject, external vendor and law-firm field work, and colour-coded case outcomes with downloadable reports.
Read case studyAreas I go deep in
Generative and agentic AI wired into real business systems — RAG pipelines, multi-agent workflows, LLM integration, and MCP tooling that automate decisions and operations instead of sitting beside them.
Fifteen years designing ERP, HRMS, background-verification and industry platforms — domain modelling, clear service boundaries, and migration paths that keep large systems changeable.
Seven-plus years running production infrastructure on AWS, Azure and Digital Ocean — containerised workloads, CI/CD pipelines, and observability that make deploys boring.
End-to-end product delivery — TypeScript across the stack, React/Next.js front ends, and Node, Java or Python services, from schema to ship.
Authentication, authorisation and data protection built in from the start — OAuth/JWT flows, role-based access, secrets management, and compliance-ready audit trails.
REST and event-driven APIs other systems can build on — versioned contracts, webhooks, third-party integrations, and a developer experience that does not need a support ticket.