I build AI and data products at the intersection of product strategy, systems thinking, and human-centered problem solving.
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I work where product strategy, analytics, and emerging AI systems meet.
My background spans software engineering, business intelligence, and product ownership — which means I naturally move between the technical details and the decisions they enable.
I'm especially interested in products that take something complicated — data, workflows, systems, or AI — and make it easier for people to understand and act on.
From building dashboards to owning AI applications, I've consistently worked on the same problem: turning information into better decisions.
/02 — Movement
01
Born here
02
First move
03
New language, new rules
04
A different continent
05
Back, but not the same
06
Smaller, slower, new again
Growing up
01 — 06
01
Born here
02
First move
03
New language, new rules
04
A different continent
05
Back, but not the same
06
Smaller, slower, new again
I got used to being new.
New places. New people. New ways of doing things.
I learned to observe first, understand quickly, and find my way through unfamiliar environments.
Then, a decision
Columbia University
New York · 2025
This time, I chose it.
I came to Columbia to deliberately expand the way I understand products.
I wanted to understand not just how products are built, but how data, technology, users, and product decisions come together.
I came to Columbia to deliberately expand the way I understand products.
I wanted to understand not just how products are built, but how data, technology, users, and product decisions come together.
/03 — Instinct
/01
When something is unfamiliar, I pay attention before I try to change it.
/02
I want to know how the pieces fit together before deciding which piece needs fixing.
/03
I naturally look for relationships between people, information, systems, and decisions.
/04
Once I understand a system, I start asking why it works the way it does.
/03 — Instinct
01 — 04
/01
When something is unfamiliar, I pay attention before I try to change it.
/02
I want to know how the pieces fit together before deciding which piece needs fixing.
/03
I naturally look for relationships between people, information, systems, and decisions.
/04
Once I understand a system, I start asking why it works the way it does.
/04 — Intent
I didn't take a straight path into product.
Engineering → Analytics → Product → AI. Each move was a perspective I wanted.
/01
Software Engineering
How does it actually work?
I learned how products are built — how systems behave, where things break, and what happens underneath the interface.
/02
BI Development / Analytics
What does the data tell us?
I learned to connect operational data with the decisions people actually needed to make.
/03
Product-oriented ownership
What should we build, why, and for whom?
My scope expanded from building and analyzing to making product decisions, prioritizing work, aligning stakeholders, and thinking about what should exist in the first place.
/04
AI Product Management
What changes when the technology itself can retrieve, reason, generate, and act?
My AI product work brings the technical, analytical, and product perspectives together.
Engineering → Analytics → Product → AI
/01
Software Engineering
How does it actually work?
I learned how products are built — how systems behave, where things break, and what happens underneath the interface.
/02
BI Development / Analytics
What does the data tell us?
I learned to connect operational data with the decisions people actually needed to make.
/03
Product-oriented ownership
What should we build, why, and for whom?
My scope expanded from building and analyzing to making product decisions, prioritizing work, aligning stakeholders, and thinking about what should exist in the first place.
/04
AI Product Management
What changes when the technology itself can retrieve, reason, generate, and act?
My AI product work brings the technical, analytical, and product perspectives together.
Then it converges.
/05 — Three roles
JLL Technologies·Software Engineer · BI Development Analyst·3 Years
I started as an engineer shipping features.
I moved into BI to understand the gap between operational data and the decisions real estate teams needed to make.
Later, my scope expanded into product-oriented ownership across AI-driven applications — including roadmap thinking, prioritization, stakeholder alignment, and product decisions.
Three roles.
One thread.
Understanding what a product actually needs.
Product
I didn't build my career around titles.
I built it around perspectives.
/07 — Selected work
Products and systems where I owned decisions, not just deliverables.
This is where the pieces come together.
01/Brillio HLS·AI PM Intern·3 Months
A multi-agent system that reconciles patient records across incompatible healthcare vocabularies.
View case study02/JLL Technologies·Software Engineer · BI Development Analyst·3 Years
From writing the pipelines to owning the insight — closing the gap between data and the decisions it should drive.
View case study03/Columbia University·GenAI Course Project·Team of 4
A multi-agent event discovery app — I owned retrieval and ranking.
View case studyEnd of sequence
Three projects are only part of the story.
View all work/08 — Method
Moving through unfamiliar environments taught me to understand before I act. I bring the same instinct to product problems.
/01
Start with the problem, not the solution.
I clarify the user, business, technical, and operational constraints before deciding what to build.
/02
Separate the important from the interesting.
I use data, research, stakeholder conversations, and system behavior to understand where the real opportunity is.
/03
Understand how the pieces connect.
I map workflows, data dependencies, technical constraints, and AI capabilities before committing to an approach.
/04
Choose what matters now.
I prioritize based on impact, feasibility, evidence, and what the product actually needs to prove.
/05
Turn decisions into something real.
I work closely with engineering and design, prototype quickly, and test assumptions before they become expensive.
/06
Ship, measure, and improve.
I treat launch as the beginning of the learning loop rather than the end of the product process.
/08 — Method
Moving through unfamiliar environments taught me to understand before I act. I bring the same instinct to product problems.
01 — 06
/01
Start with the problem, not the solution.
I clarify the user, business, technical, and operational constraints before deciding what to build.
/09 — Focus
01 / 12
/10 — Toolkit
The tools I use to turn ambiguity into something teams can act on.
/11 — Principles
Don't automate a bad workflow.
Build the smallest system that proves the idea.
Data is useful when it changes a decision.
AI should reduce cognitive load, not add to it.
Product decisions are also decisions about what NOT to build.
Where I've been
What I've learned
What I've deliberately built
A rounded view of product is something I built one perspective at a time.
Where I've been
What I've learned
What I've deliberately built
A rounded view of product
is something I built
one perspective at a time.
/12 — What's next
I've spent my career deliberately collecting perspectives.
Engineer. Analyst. Product thinker. AI builder.
I'm not looking to choose one and forget the others.
I'm looking for products where all of them matter.
/13 — Contact
If you're working on a difficult product problem, an AI system, or a decision that needs better data behind it, I'd love to talk.