Building a fintech product?

You don't need another developer. You need a technical partner.

I build serious web products for founders. AI accelerates every part of my process, but architecture and engineering judgment are what make the product hold up.

FINTECH SAAS DATA TRADING AI COMPLEX WEB APPLICATIONS

The Problem

The problem isn't building software anymore.

AI can generate a lot of code. A founder can describe an idea, open a coding tool, generate a UI, wire up a database, add auth, integrate an API, and have something that looks like a product within hours.

But the difficult part of building a serious product isn't generating code.

It's deciding:

What should the architecture look like?
Where does business logic live?
What belongs in the database?
How should data flow through the system?
What happens when requirements change?
How should authentication and authorization work?
How should sensitive financial data be protected?
How should external APIs be integrated?
What happens when the product grows?
How should the system be tested?
How should it be deployed?
How do you know AI didn't quietly create a structural problem?

AI can write the code.

Someone still has to design the system.

Two Approaches

Vibe Coding Prompt → Code
AI-First Engineering Architecture → Specification → AI → Code
Vibe Coding Optimize for immediate speed
AI-First Engineering Optimize for speed + durability
Vibe Coding Feature-by-feature
AI-First Engineering System-by-system
Vibe Coding AI decides implementation
AI-First Engineering Technical partner defines constraints
Vibe Coding Architecture emerges accidentally
AI-First Engineering Architecture is intentional
Vibe Coding Problems are fixed later
AI-First Engineering Failure modes are considered early
Vibe Coding Prototype mindset
AI-First Engineering Production mindset
Vibe Coding Generated code is the output
AI-First Engineering Working software is the output

I don't use AI instead of engineering.

I use AI to make engineering faster.

Why Fintech

Fintech changes the equation.

A landing page can survive ugly code for a while. A fintech product can't.

When your application handles:

Money Financial data Market data Transactions User permissions External financial APIs Complex calculations Sensitive customer information Asynchronous processes

architecture isn't an academic exercise.

It becomes part of the product.

I've been building software around financial markets, quantitative systems, trading, market data, and analytics for years. That background shapes how I think about product engineering.

See How I Approach a Fintech Product

Experience

Financial Systems

Trading, options, market data, quantitative workflows.

Data Systems

Large datasets, time-series data, analytics and data pipelines.

Product Engineering

Complex SaaS and web applications.

AI-First Development

Using AI to move faster on architecture, implementation, testing, and iteration.

Cloud & Infrastructure

Production infrastructure, APIs, databases, authentication, storage and deployment.

See How I Work

The Process

What happens after you hire me.

You are not buying development hours. This is a product engineering process. We go from concept to working software, using AI to move fast while keeping the architecture under control.

~8 min
01

From Idea to System

Before writing code, we figure out what we're actually building. We define the users, workflows, domain, data, integrations, constraints and risks.

Next: Architecture
~10 min
02

Architecture Before Implementation

The goal isn't to create a pile of features. The goal is to create a system where those features make sense together.

Next: AI-First Development
~12 min
03

AI Doesn't Replace Engineering

AI is most useful when it operates inside constraints set by someone who understands the system. This is how AI fits into the process without replacing the person responsible for it.

Next: Vertical Slice
~9 min
04

Build the System Before Building Everything

The first milestone is one complete path through the system. Authentication, database, business logic, API, UI. If the architecture works end to end, everything else is incremental.

Next: Production
~11 min
05

Prototype → Production

What separates a prototype from production software. Security, testing, deployment, observability, and the work that makes the thing actually reliable.

Tell me about your product

Technical Partner

You don't need a CTO full-time.

Most early stage companies don't need a full engineering org. They need one person who can own the technical side of the product while the company figures out everything else.

Architecture

Design the technical foundation and make critical technical decisions.

Product Engineering

Turn product requirements into working software.

AI-First Development

Use AI aggressively while maintaining architectural and technical control.

Technical Leadership

Help determine what should be built, when, and why.

Infrastructure

Own the systems required to run the product.

Security

Design authentication, authorization and data handling appropriately.

Integrations

Connect the product with external APIs and services.

Scaling

Prepare the architecture for the next stage of the company.

The Retainer

A technical partner, not another pair of hands.

You run the business and the product. I own the technical side. That means architecture, implementation, infrastructure, and the decisions that keep the system working as it grows.

+ Technical ownership
+ Product development
+ Architecture
+ Decision making
+ AI-accelerated implementation
+ Continuous improvement
Let's talk about what you're building

Get Started

Tell me what you're building.

Give me enough context to understand the product, where you are today, and where you need technical help.

AI makes development faster.

Architecture makes development sustainable.

The combination is what creates leverage.