AI | .NET & Full-Stack Developer | Next.js | Flutter
Web & Mobile Developer | React Node ASP.NET Vue React Native
Lead Full Stack Developer | AI/ML Engineer | Data Scientist
New to Contra
Lead Full Stack Developer | AI/ML Engineer | Data Scientist
Build & Fix Complex .NET Systems, APIs & Workflows
Build & Fix Complex .NET Systems, APIs & Workflows
Technical Pricing Platform – Excel to Scalable Web Application
Led development of a technical pricing platform at MS Amlin, transforming Excel-based actuarial models into scalable web applications used by underwriters and actuaries.
The platform standardised pricing workflows, improved consistency across models, and enabled better usability and governance of complex pricing logic.
Worked closely with senior stakeholders, mentored developers, and delivered a maintainable architecture focused on reliability, data integrity, and long-term scalability.
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SIPP Onboarding Platform – API-Driven Web Application
Led development of a paperless SIPP onboarding platform for Tilney Smith & Williamson, integrating with Embark APIs to automate client onboarding, AML screening, and account creation.
The platform reduced account opening time from days to minutes and also integrated card payments, the SEI wealth platform, and SIPP transfers.
Built a robust, maintainable .NET backend and responsive UI with full API connectivity and a strong focus on straight-through processing.
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Enterprise Royalty Management System & Financial Workflows
Contributed to the development of an enterprise Actuarial Modeling Platform used by insurers for risk analysis and Solvency II compliance.
Worked on a secure, workflow-driven system handling complex financial models and large data processing. Delivered full-stack features, built and maintained APIs, and supported integration with a high-performance C++ calculation engine.
Focused on system reliability, role-based access control, and enabling scalable model execution for enterprise users.
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Actuarial Modeling Platform for Insurance Risk & Solvency II
Contributed to the development of an enterprise Actuarial Modeling Platform used by insurers for risk analysis and Solvency II compliance.
Worked on a secure, workflow-driven system handling complex financial models and large data processing. Delivered full-stack features, built and maintained APIs, and supported integration with a high-performance C++ calculation engine.
Focused on system reliability, role-based access control, and enabling scalable model execution for enterprise users.
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AI Agents & Automation That Ship | Voice AI, LLMs, .NET
Not every automation needs an LLM. A B2B business was receiving purchase orders from retailers through SPS Commerce.
Someone on the team then checked stock by hand, retyped each order into Sage 50 as a sales order, and kicked off fulfillment.
We built a platform on ASP.NET (http://ASP.NET) Core and C# that handles it end to end.
→ Purchase orders come in through SPS Commerce automatically
→ Stock and order details are validated before anything is created
→ Sales orders land in Sage 50 without retyping
→ Anything odd is flagged as an exception instead of quietly slipping through Less manual work across the whole order lifecycle, cleaner data, and orders that keep moving without anyone copying fields between screens.
I build a lot of AI agents now. But the first question on every scoping call is still the same.
Does this need judgement, or does it just need wiring? Half the time it's wiring.
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Most AI features never leave the demo.
The model is rarely the problem. It's everything around it: messy data, old .NET code nobody wants to touch, and no clear answer to "what does this actually save us?"
On CasePath we skipped the chatbot and aimed AI at one job caseworkers hated: writing case notes.
Result: 90% less documentation time. Supervisor decisions 83% faster. 20% more caseload with zero new hires.
What made it work:
Pick one painful task, not a whole "AI strategy"
Put AI inside the app people already use
Measure hours saved before writing a line of code
If you run a .NET product and AI is on your roadmap, message me. One call and I'll tell you where it'll pay off, and where it won't.
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An AI agent that can move money is only useful if it can't move it on its own.
Haia lets people manage their banks, crypto wallets and brokerages from one place, just by saying what they want done.
I built the AI orchestration layer. The interesting design choice wasn't the model. It was deciding where the model is not allowed to act.
→ The agent turns a request into a step by step plan
→ Each step is routed to the right banking API, wallet, chain or brokerage
→ Security and compliance checks run before anything executes
→ The user approves every move, and transactions are signed on their own device It's fully non-custodial.
Zero private keys ever exposed, to us or to the model.
If you're building agents that touch money, health records or anything you can't undo, design the approval step first. Then the AI.
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Senior .NET developer – API & ERP integrations, n8n & AI
New to Contra
Senior .NET developer – API & ERP integrations, n8n & AI
Senior Lead Graphic Designer | UI/UX & Product Engineer
New to Contra
Senior Lead Graphic Designer | UI/UX & Product Engineer
Backend Developer
Backend Developer
