ex–Customer Success & Service Delivery Manager → Full-Stack Product Developer
✨ from kickoff decks & QBRs to deployment pipelines - finally fixing the features I used to file tickets for ˗ˏˋ☕ˎˊ˗
˗ˏˋ ꒰ ✉︎ ꒱ ˎˊ˗ LinkedIn | ⁴⁰⁴ GitHub
i started on the other side of the ticket queue - leading back-to-back client meetings, training teams, running adoption audits, and pretending my Wi-Fi could handle one more Loom recording.
after years helping SaaS teams and marketplaces ship big, messy launches, I swapped onboarding checklists, delivery decks, and QBR meetings for designing, refactoring, and re-imagining systems - helping build the very platforms I once helped businesses grow on.
now that I've become the engineer I used to chase in Slack, i care about the small, intentional choices that make products feel human - the kind that turn predictability into confidence and usability into trust.
the harsh reality is that most users never see the complexity of systems at scale - or the effort it takes to keep them from crashing - but they FEEL when a product cares about helping them reduce overhead, drive sales, or simply win a few hours back in their day.
working with business users - from small teams to large-scale enterprises - has taught me how small decisions ripple: how a setting’s behavior can shape business logic, how a page’s load time can affect trust, and how missing guidance can quietly slow someone’s day.
over time, I’ve seen how these moments - good or bad - compound into something larger: the kind of experience that earns renewal, or the kind that quietly drives churn.
i build with that in mind.
my focus is on systems that are calm under pressure, transparent in behavior, and kind to those who rely on them. i like when design and engineering meet halfway - when a schema, a test, or a log line reflects thoughtfulness, not just functionality.
my background in customer success and delivery keeps me grounded in outcomes.
it’s given me a front-row view of how organizations think, where friction lives, and why some products earn loyalty while others fade. it reminds me that building something sticky means solving real problems with empathy - and that good engineering carries a quiet confidence - seen not in how much it does, but in how well it endures.
🚨 pleaaaase feel free to drop me a DM on
bulding systems that are dependable, thoughtful, and made to last is important to me.
Languages & Frameworks:
i build applications that balance structure and simplicity.
most of what I build is centered on predictable, maintainable design - code that’s easy for others to read, extend, and trust.
i enjoy working across the stack and finding the small architectural decisions that make large systems feel intuitive.
***familiar with large Ruby on Rails monoliths (Majestic Monolith architecture) and their GraphQL API layers - comfortable reading controllers, models, and data flows to understand domain behavior
Databases & ORM:
i try to design data models that reflect real-world logic as much as business rules.
for me, a good schema makes collaboration easier - when data makes sense, conversations do too.
i believe that clarity in data design quietly supports every feature that depends on it.
Tools:
i set up tests and pipelines to make progress steady and dependable.
testing is something I enjoy because it helps the team move quickly without fear of regression.
my focus is on small, consistent safeguards that build trust over time.
Tools:
working with infrastructure keeps me close to how code actually lives in production.
i like the rhythm of building, deploying, and observing how systems behave in real environments.
my goal is to make deployment and maintenance feel calm and repeatable - not a source of anxiety.
Tools:
for me, understanding performance and behavior early helps prevent noise later.
i enjoy integrating visibility into systems - logging, metrics, tracing - so issues surface clearly and recovery is faster.
there’s a quiet satisfaction in seeing a system tell you what it needs before something breaks.
Tools:
i’m drawn to how data and automation can help products make smarter decisions.
i’ve been exploring modern data pipelines and AI integration to understand how insights can flow naturally into the product experience.
my focus is on connecting information to impact - both for teams and users.
Tools:
i like when documentation and delivery feel seamless with development.
i keep my work visible and well-documented so others can build on it easily.
for me, communication is a kind of infrastructure - it keeps everything running smoothly.
tl;dr: i care about systems that age well - in their design, their data, and in how people work with them every day.
a web app that figures out your face shape, skin undertone, and color season - then pairs it with fashion and makeup recommendations that actually make sense.
your “AI-powered personal stylist,” but with less judgment and faster response time.
- frontend: HTML5 · CSS3 · Vanilla JavaScript
mobile-first, responsive, and optimized with the Canvas API for real-time image compression and rendering
- AI engine: Google Gemini 2.5 Flash - handles image understanding, facial geometry, color theory, and text generation in one shot
- content Layer: Pexels API - for fetching contextual, high-quality fashion inspiration (no more mannequins from Unsplash 😅)
- networking & Logic: Fetch API · Asynchronous orchestration with proper error handling and defensive coding
- performance Optimizations:
- Image compression (≈90% smaller) via
canvas.toDataURL('image/jpeg', 0.2) - Cached DOM references for buttery-smooth UI
- Smart fallback logic for API rate limits and JSON repair
- Image compression (≈90% smaller) via
- reduced API cost by 85% and response time by 60% after migrating to Gemini 2.5 Flash:contentReference[oaicite:0]{index=0}
- one unified multimodal request handles facial recognition, color analysis, and recommendation generation
- defensive error handling for markdown wrappers, token truncation, and service downtime - because AI APIs will misbehave
- progressive loading: main analysis first, fashion images stream in later for that “Netflix loading bar” feel
🧩 brings together everything I love - data, design, and human-centered technology. also, it finally justifies the hours I’ve spent color-matching code editors to my desktop wallpaper.