01 · Platform
Scalable product platforms
Multi-tenant SaaS architected to survive 100× growth: system design, data modelling, async workflows, delivery pipelines and the infrastructure underneath them.
Next.jsTypeScriptPostgresPrismaSupabase
19
Hello, I'm Lucas de Moraes Tiberio
I build scalable products & the agent systems that run them.
Currently buildingscalable platforms
Senior Software Engineer and AI Engineer. 7+ years shipping scalable platforms and backend, frontend and AI systems — and putting production AI agents on the road with the evals, guardrails and telemetry that keep them there.
São Paulo, Brazil · UTC−3 · US & EU overlap
Agent telemetrysynthetic feed
Throughputp95 latencyTask success
Runs / min130
p95 latency780ms
Success87.0%
The brief — what I build
Three things, all shipped in production.
Every offer below maps to systems now running for real users — not side projects.
02 · Agents
Production AI agent systems
GenAI agents that take real actions in real systems: prompt and tool design, structured reasoning, RAG, integration architecture, security and guardrails on every write path.
PythonFlaskLLMsRAGTool designGuardrails
03 · Telemetry
Evals & observability
The part most teams skip. Evaluation workflows with daily reporting, metrics across agent behaviour and task outcomes, execution logging and idempotent safeguards for recovery.
EvalsMetricsAudit logsIdempotency
Setup sheet — how an agent ships
How an agent gets to the grid.
A fast lap is set up before it is driven. Same with agents — the order matters, and skipping a line shows up later as an incident.
01
Spec the workflow, then the failure modes
Write down what the agent is allowed to accomplish and every way it can be wrong, before a single prompt exists. The failure list becomes the eval suite.
02
Build the integration surface
Typed tools against real systems, least privilege by default. The agent reasons; the backend decides what is actually possible.
03
Constrain the write paths
Guardrails and idempotent safeguards on anything that changes state, so a retry or a bad turn cannot double-book, double-charge or corrupt a record.
04
Score it on a schedule
Evaluation workflows that grade behaviour, outcomes and workflow execution daily — regressions get caught by a report, not by a customer.
05
Instrument for traceability
Execution logging and metrics end to end, so any run can be replayed, explained and recovered. Telemetry is what turns a demo into an operable system.
Sector times — results and scale
Shipped, and measured.
Numbers from systems I designed, owned or scaled. Purple marks a career best.
7+Years shipping production software, from frontend at scale to production AI systems
BEST500K+Monthly users across the luxury storefronts I built on at Farfetch
BEST10×Growth in monthly users on the platform I architected at Campground — from hundreds to more than 10,000 inside a year, as its first engineering hire
10K+Monthly users the multi-tenant SaaS reached — Next.js, TypeScript, PostgreSQL, Prisma and Supabase
1,000+Developers relying on the core frontend library I supported at Farfetch
6Industries shipped in — e-commerce, healthcare, education, CRM, workforce management and software houses
Constructors
Simbie AICampground SystemsFarfetchGrupo Fleuryb8oneDoDev SchoolPresent TechnologiesVerzelPhobos Tecnologia
Race history — experience
Nine stints, 2019 to now.
Gold is the current stint. Bars overlap where I ran more than one engagement at a time.
2019 — 2027zoom in to pan
201920202021202220232024202520262027
- Build and operate production AI agents for healthcare practices, automating patient workflows — scheduling, rescheduling, cancellations, confirmations, insurance screening and escalation to clinical staff — through direct EHR integrations.
- Build Python backend systems that let agents interact securely with external platforms and execute clinical workflows, with security and guardrails, scalable design patterns and integration architecture aligned to compliance requirements.
- Design and evolve GenAI agent systems: prompts, tools, context engineering and interaction workflows that enable structured reasoning, safe system actions and reliable task execution in production.
- Defined evaluation workflows for production agents, generating daily performance reports and tracking metrics across agent behaviour, call outcomes and workflow execution.
- Established observability and auditing: execution logging, metrics tracking and idempotent safeguards for traceability, failure recovery and reliable operations.
AI AgentsPythonFlaskTypeScriptPostgreSQLPrompt engineeringLLMRAGContext engineeringAgent evaluationVoice agents
- First engineering hire — took platform adoption from hundreds to over 10,000 monthly users within a year by defining system architecture and product direction with leadership, translating customer needs into scalable solutions while weighing performance, cost and extensibility.
- Designed and evolved the company's multi-tenant SaaS platform on Next.js, React, TypeScript, PostgreSQL, Prisma and Supabase, establishing architectural patterns and multi-environment delivery.
- Drove the evolution of multiple codebases as the business scaled, strengthening architectural consistency, development workflows and system reliability while reducing technical debt.
- Owned platform infrastructure and production reliability: DNS and networking, secure tunnelling, backend API infrastructure, domain routing, email authentication (SPF/DKIM/DMARC) and environment isolation.
- Established automated CI/CD across development, staging and production, improving release safety and enabling rapid, reliable iteration.
- Architected core platform communication and operational systems, including asynchronous notification infrastructure, audit-ready activity tracking and spreadsheet-style data interfaces for large-scale operational workflows.
- Onboarded and mentored engineers as the team grew, writing the technical documentation and establishing the development patterns that held across codebases.
- Worked directly with customers to align technical feasibility with business priorities, balancing immediate delivery against long-term platform sustainability.
- Applied AI across product and engineering workflows to accelerate prototyping, feature implementation and system evolution.
AIDenoPythonFlaskTypeScriptNode.jsSQLSupabaseReactNext.jsTailwindCSSPrismaCypress
- Structured the full curriculum for a front-end development track, covering React, advanced React, project structure, hooks, custom hooks, Context API, Redux and unit testing with Jest and React Testing Library.
- Created and recorded a real-time development course on WebSockets, covering pub/sub patterns and the web architecture of socket-based software alongside the programming itself.
ReactWebSocketsJestReact Testing LibraryReduxTeaching
- Contributed to over 10 luxury e-commerce platforms and codebases, building global applications with Node.js and React.
- Supported and evolved a core frontend library used internally by over 1,000 developers, centralising Redux state, GA4 tracking, themes, HTTP requests and shared configuration.
- Configured projects and internal packages with Module Federation across a monorepo, using Webpack and Razzle.
- Wrote the documentation and architecture diagrams for the features I shipped, so the project and its internal packages stayed legible as they scaled.
- Researched and integrated international payment gateways: Apple Pay, iDeal, PayPal and Klarna.
- Refactored business-critical legacy code and proved the gains with PageSpeed, auditing discontinued, redundant and unused dependencies.
- Built scalable GA4 event tracking through Redux middlewares, HOCs and hooks, and wrote unit tests across routing, store, translations, React state and CMS integration.
JavaScriptTypeScriptNode.jsReactModule FederationWebpackRazzleGA4SEOA/B testsJenkins
- Owned technical feasibility, quality and infrastructure for a product line, aligning expectations against designs and business rules.
- Designed and built a React UI design system with the design team, organising component diagramming around scalability, responsiveness and visual intent.
- Created production, staging and development cloud environments — DigitalOcean droplets wired to CI/CD pipelines — and deployed both backend and frontend applications.
- Boosted API query performance by 80% with a Redis-based caching layer.
- Supported other developers directly, starting 1:1s, pair programming and a technical progression track.
JavaScriptTypeScriptNode.jsPostgreSQLGraphQLRedisDigitalOceanNginxCI/CD
- Developed websites and SSR applications with Next.js and React for one of the largest healthcare platforms in Brazil, plus proofs of concept for technical decisions.
- Built Node.js microservices and real-time integrations with sockets (Pusher).
- Applied and maintained the internal design system, ran code reviews and contributed to epic-level analysis and solution research.
- Wrote frontend tests across complete flows integrated with Redux, Context API and Axios, covering requests, layout and responsiveness.
- Created and refactored end-to-end tests with Cypress against the Next.js frontend.
JavaScriptTypeScriptNode.jsNext.jsReactReduxWebSocketsPusherCypressJest
- Owned full-stack maintenance and built new platform features in React with Redux and TypeScript, integrated with GraphQL and styled with Styled Components.
- Created REST and GraphQL APIs in TypeScript over PostgreSQL, MongoDB and Redis, including VTEX, Loja Integrada and Iugu integrations.
- Delivered a visual rebrand, architecting components and maintaining flows alongside UX.
- Applied mobile-first design, TDD and DDD within Scrum and Kanban.
- Maintained and extended a core affiliate platform, improving product and affiliate management, activity logging and reporting.
- Built e-commerce plugins for abandoned carts and remote affiliate selling, feeding directly into sales recovery and channel expansion.
DDDGraphQLJavaScriptMobile-firstMongoDBNode.jsPostgreSQLRedisStyled ComponentsTDDTypeScriptVTEX
- Built sites and single-page applications with React and Redux, plus responsive, scalable systems in C#.
- Created and integrated REST APIs and wrote unit tests with Jest, working in Scrum with Git and GitFlow.
- Ran delivery in Scrum with Git and GitFlow, tracking work in Jira across concurrent client projects.
C#GitGitFlowJavaScriptJestRESTReactReduxScrum
- Maintained and enhanced a digital time-tracking platform in HTML, CSS, JavaScript and jQuery, contributing frontend and backend features that streamlined daily employee logging and management for clients.
- Worked across MVC and Classic ASP with SQL, with a focus on user interface and experience.
HTMLCSSJavaScriptjQueryMVCClassic ASPSQL
Education
Technologist, IT ManagementFaculdade ENIAC · Brazil · 2019 – 2021
High School DiplomaColégio Integrado de Guarulhos · Brazil · 2016 – 2018
Certifications & courses
AI Agents and Agentic AI with Python & Generative AI
Certified HTML Developer
Certificate of Competence in English
Languages
PortugueseNative
EnglishFull professional
SpanishProfessional working
The garage — stack and tools
What's on the tool trolley.
Everything here has been used to ship something someone paid for.
AI & agents
- AI agents
- Prompt engineering
- LLMs
- Generative AI
- RAG
- Context engineering
- Tool design
- Guardrails
- Agent evaluation
- Voice agents
Backend
- Python
- Flask
- Node.js
- TypeScript
- Deno
- Express
- GraphQL
- REST
- WebSockets
- Microservices
- C#
Frontend
- React
- Next.js
- Redux
- TailwindCSS
- Styled Components
- Module Federation
- Webpack
- Razzle
- Angular
- Micro-frontends
- SSR
Data
- PostgreSQL
- SQL
- Prisma
- Supabase
- Redis
- MongoDB
- Firebase
- MariaDB
Infrastructure
- AWS (EC2, S3, CloudFront, Route 53)
- DigitalOcean
- Docker
- Nginx
- Linux
- GitHub Actions
- Jenkins
- Azure DevOps
- CI/CD
- SSL / DNS
- SPF / DKIM / DMARC
Quality & telemetry
- Jest
- Cypress
- TDD
- DDD
- Datadog
- Sentry
- Code review
- A/B testing
- Google Analytics 4
- SEO / JSON-LD
- Lighthouse
Pit radio — hire me from an agent
Brief me from your agent.
If you're screening engineers with an LLM, give it this instead of a PDF. It's the same information a recruiter would ask for, in a shape a model can actually use — scope, stack, location, and how to reach me.
No hidden endpoint, no scraping tricks. Paste it into Claude, ChatGPT or your own harness.
AGENTS.md
# AGENTS.md — Lucas de Moraes Tiberio # Senior Software Engineer / AI Engineer # São Paulo, Brazil · UTC−3 · overlaps US & EU role: Backend & AI Engineer, Simbie AI (New York, US) experience: 7+ years across 8 companies education: Technologist, IT Management — Faculdade ENIAC languages: Portuguese (native), English (full professional), Spanish (professional working) builds: - scalable multi-tenant SaaS platforms - production GenAI agent systems (prompts, tools, guardrails) - evaluation harnesses & observability for agents - backend integration architecture under compliance constraints core_stack: Python, Flask, TypeScript, Node.js, Next.js, React, PostgreSQL, Prisma, Supabase, Redis, GraphQL, AWS, Docker domains: healthcare workflows, luxury e-commerce, multi-tenant SaaS, developer tooling, education contact: email: ltiberio55@gmail.com linkedin: linkedin.com/in/lucas-tiberio # To start a conversation: email the address above with # what you're building, the scope, and your timeline.
Driver briefing — questions answered
What to know before hiring me.
Backend-leaning full-stack, now spending most of my time on AI systems. Seven years took me from frontend at scale, through founding-engineer platform architecture, to production agent systems. I am comfortable owning a feature from data model to deployment.
São Paulo, Brazil, UTC−3. I have worked for United States companies for over two years and shipped from Portugal for Farfetch, so US and EU overlap is normal for me. I work in Portuguese, English and Spanish. Email is the fastest way in.
All the way to DNS. As founding engineer at Campground Systems I owned platform infrastructure and production reliability end to end: DNS and networking, secure tunnelling, domain routing, email authentication (SPF/DKIM/DMARC), environment isolation, and automated CI/CD across development, staging and production.
Yes — healthcare, on both sides of my career. I build backend systems that let agents interact securely with external platforms and execute clinical workflows, with security, guardrails and integration architecture aligned to compliance requirements. Earlier, I built microservices and SSR applications for one of the largest healthcare platforms in Brazil.
Yes. I onboarded and mentored engineers as Campground scaled, wrote the technical documentation and set the development patterns that held across codebases. At b8one I started 1:1s and pair programming, at Farfetch I supported a library used daily by more than 1,000 developers, and I have taught React and WebSockets as a course instructor.
Pit lane — get in touch
Got something that needs to scale?
Platforms, agent systems, or the telemetry to prove either one works. Tell me what you're building and where it's hurting.