I build complex digital products and the systems that help teams ship them.
Turning ambiguous ideas and operational workflows into intuitive, production-ready software. My work spans frontend architecture, product design, full-stack implementation, AI-native development systems, and cross-functional technical leadership.
Production work across product and AI-native delivery.
Greenfield Build Harness
Problem statement: Ad hoc AI-assisted development drifts: skipped planning, architectural drift, inconsistent output, weak verification, and handoffs that don't survive past a single session.
Sunra Health
Problem statement: A functional-health company needed a production platform spanning marketing, checkout, personalized pediatric health profiles, and genetic-report delivery with evolving business and health requirements throughout.
Trellis
Problem statement: I wanted a way to manage my own garden in a very specific way and wasn't happy with any of the existing options. That gap became Trellis: a system built around what needs attention now, not just what I planted.
Closetcore
Problem statement: I built Closetcore for my teenage stepdaughters: a simple closet organizer and outfit planner that stays calm, avoids overstimulation, and has absolutely no social component — something that was surprisingly hard to find in existing apps.
Where I add the most leverage.
Product Engineering
Taking products from ambiguous requirements through architecture, implementation, QA, deployment, and iteration.
Frontend Architecture
Building scalable React and Next.js applications, complex workflows, reusable component systems, responsive interfaces, and maintainable frontend foundations.
AI-Native Delivery
Designing agent harnesses, shared repository knowledge, reusable skills, review gates, verification workflows, and productive human-agent collaboration.
Technical Enablement
Helping engineers, clients, and nontechnical teams understand systems, make better decisions, and become more independently capable.
Structure is what turns speed into something you can trust.
Every project, with or without AI in the loop, runs through the same discipline: research the real system, plan before building, implement against that plan, and verify before it ships.
- Start with the real user problem.
- Understand the system before changing it.
- Reduce ambiguity through research and planning.
- Ship working software iteratively.
- Design for maintainability and handoff.
- Use AI to increase capacity without lowering standards.
- Treat documentation as part of the product.
- 1Research
- 2Plan
- 3Implement
- 4Verify
A product engineer's approach to engineering.
I’m CiaraMaria, a senior product engineer, technical leader, and Certified ScrumMaster who likes turning complicated, half-formed ideas into products that feel clear, thoughtful, and genuinely useful. I’ve built across health, commercial aviation, ecommerce, food retail, and Web3, often in environments where the requirements are changing and the path forward has to be discovered while the work is already underway.
I'm especially drawn to meaningful and mission-driven work.
More about me