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Lorenzo Leão Dotto

Full-Stack Developer

TypeScript · React/Next.js · Node · PostgreSQL

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Summary

Full-stack developer who ships complete products end to end — data model, security boundaries, interface and deploy. Built and shipped an offline-first operations system used daily by field crews, and a data product with client-side machine learning. Comfortable putting business rules where they can't be bypassed, and disciplined about not claiming results that haven't been measured.

Fluent Portuguese, working English (improving through full-time study in Brisbane).

Technical skills

Languages
TypeScript, JavaScript, Python, SQL
Frontend
React 19, Next.js 16 (App Router), Tailwind CSS v4, shadcn/ui, PWA, GSAP
Backend
Node.js, Fastify, Next.js Route Handlers & Server Actions
Data
PostgreSQL, Supabase (RLS, triggers, RPCs), Prisma
Testing
Playwright (E2E), Vitest, Supertest, TDD
Tooling
Docker, Git, GitHub Actions, Vercel, ESLint/Prettier, Husky
Other
transformers.js (in-browser ML), Web Push/VAPID, Google Places API, i18n

Experience

Full-Stack Developer · Sirtec

September 2025 – May 2026 · Brazil

Electrical grid construction and maintenance contractor. Sole developer on Torre Ativa, a field presence and operations system for crews working across dispersed grid sites.

  • Built an offline-first mobile presence app for field crews working in areas with unreliable connectivity — designed for two taps and no training, because the users were electricians on towers, not office staff.
  • Delivered a live supervisor dashboard with alerts, replacing a process that ran on phone calls and memory. Supervisors moved from reviewing yesterday to acting on now.
  • Produced the company's first operational dataset on crew presence and movement — information that had never been captured before, now used as the basis for planning.

Stack: Next.js, TypeScript, Supabase, PostgreSQL, Vercel. Deployed and in daily use.

Not claimed

Impact figures for this system exist but have not yet been independently verified, so they are deliberately omitted rather than estimated. Happy to walk through the architecture and the measurement plan.

Projects

FinRadar

Multi-bank statement analyser with in-browser ML

Next.js 16 · Supabase · transformers.js · Recharts

Upload bank statement CSVs from any institution and see categorised spending, with no manual tagging and no cloud AI cost.

  • Designed a format-adapter architecture: heuristic detection dispatches to per-bank parsers that normalise to one schema, so supporting a new bank is one new file with no pipeline change.
  • Built rules-first categorisation achieving 93% coverage on the reference dataset, with an optional local AI layer — an embedding model running entirely client-side in a Web Worker (WebGPU with WASM fallback), paired with a classifier trained offline to ~91% validation accuracy on 68k transactions.
  • Implemented cross-file deduplication for overlapping statement periods, historical FX conversion at each transaction's own date, and full PT/EN internationalisation.

Not claimed

Used synthetic sample data rather than real statements, documented as such — reference formats were reproduced structurally, including edge cases that match no categorisation rule.

Additional work in commercial cleaning operations (Postgres RLS, locked-transaction job assignment, web push) available to discuss — repository private pending client sign-off.

Education

Technologist Degree in Systems Analysis and Development

FIAP, São Paulo, Brazil

2024 – 2025

Equivalent to an Australian Associate Degree / Advanced Diploma in Information Technology.

English Language Studies (ELICOS)

Pacific English Study, Brisbane QLD

2026 – present

Languages

Portuguese (native) · English (intermediate, in full-time study)

Availability

Available 24 hours per week (student visa work rights, 48 hours per fortnight). Unrestricted hours during scheduled course breaks. Based in Brisbane; available for remote or on-site work across AEST.