Software engineer & AI builder
I build useful
software
with AI.
I’m Brian Jean, a software engineer and technical leader who enjoys turning complex ideas into things people can use.
01 / The person behind the projects
Curious by nature.
Engineer by practice.
From the first “what if”
to something people can use.

I enjoy taking a complex idea and making it useful.
I’m a software engineer and technical leader with a background in cloud infrastructure, cybersecurity, and compliance automation. I love building practical software products from the ground up, thinking through both the experience people have and the systems that make it work.
I spend much of my free time experimenting with AI-assisted development, autonomous workflows, data analysis, and computer vision. I’m especially interested in how AI can improve engineering productivity, infrastructure, security, and real-world decision making. It helps me turn ideas into working applications quickly, while I stay involved in architecture, review, and decisions that need human judgment.
Outside of software, I enjoy astrophotography, investing and technology research, football and sports analytics, and building things around my property in Northern Michigan. That includes making maple syrup, cutting firewood, gardening, and other small homesteading projects. I like learning by doing, whether I’m building an application or something with my hands.
Cloud infrastructure
Deployment, observability, reliability, and cost are part of the design.
Security & compliance
Clear access boundaries, useful evidence, and deliberate operational controls.
Applied AI
Models and agents connected to real workflows, with testing and review around their output.
02 / Featured work
An idea, built into a system.BullyBearAI
An investment desk.
Built around evidence.
I’m building BullyBearAI to bring market research, portfolio context, and supervised execution into one thoughtful workflow.
It’s where my interests in investing, AI, and dependable cloud systems come together.
Visit BullyBearAIResearch with context.
Connect market information, filings, earnings, and investment theses with the portfolio and goals behind a decision.
See the reasoning.
Keep supporting evidence, conflicting signals, and data freshness visible. Understand what needs another look.
Stay in control.
Move toward execution through explicit approval and risk checks. Reconcile the outcome against broker records.
03 / Following my curiosity
A few more things
I’m building.
The AI Field Guide
Go from simple chats to connected tools, reusable skills, scheduled work, and longer-running agents. Examples for ChatGPT, Codex, and Claude.
Deep Space Field Notes
My Northern Michigan astrophotography, turned into an interactive observatory journal with observing context and stories from the night sky.
AWS automation experiments
Natural-language tools for exploring AWS resources, alongside experiments that use AI to summarize Lambda failures.
Also on my workbench: experimental NFL forecasting and film-review tools, and a website with an AWS foundation for a counseling practice.

Good work starts with a conversation.
Have something
worth building?
I’m interested in thoughtful conversations about AI products, cloud platforms, and turning complex problems into useful software.