About Me
I’m a Software Engineer specialized in full stack development and AI. I design, build, and deploy scalable web and mobile applications, develop AI-powered solutions, and optimize machine learning models for real-world performance. My expertise spans end-to-end system architecture, rapid prototyping, API development, cloud deployment, and implementing AI workflows from experimentation to production.
My Expertise
Experience & Projects
Software Engineer focused on productionizing ML and AI-driven features: building LLM-powered agents, serverless ML APIs, and automated testing & deployment pipelines.
Key Responsibilities:
- Engineered and productionized LLM-powered agents (ChatGPT, Claude-Sonnet, Amazon Q), improving reliability and response relevance through robust prompt orchestration and monitoring.
- Built automated testing and CI/CD pipelines for AI features, including automated test-case generation and integration tests to increase coverage and reduce regressions.
- Deployed serverless ML APIs (Python, scikit-learn on AWS Lambda) with telemetry, automated evaluation, and alerting to ensure production observability and reliability.
Technologies Used:
Architected and implemented StudyShield, an AI-powered PWA using React 18, TypeScript and Vite; delivered a responsive, installable web app with offline support and service-worker versioning.
Key Responsibilities:
- Designed and shipped a dual-mode AI platform integrating Google Gemini (Flash online + Nano offline) with streaming responses and automatic failover to ensure low latency and offline resilience.
- Integrated Supabase for Auth, PostgreSQL and Storage; authored DB migrations and Row-Level Security policies and designed user_profiles and conversations schemas to enforce per-user data isolation.
- Built secure multimodal chat: file attachments (images/PDFs via pdfjs), voice input (Web Speech API), content sanitization (DOMPurify) and AI content filtering to protect users.
- Implemented Focus Mode and distraction-blocking UX to increase study session productivity; added gamified progress tracking and analytics dashboards (Recharts) to boost engagement.
- Enforced engineering quality: strict TypeScript, ESLint, structured project layout (services/integrations/hooks), CI/deploy readiness (Vercel), and performance tuning targeting Lighthouse/Core Web Vitals.
- Implemented internationalization (react-i18next), accessible UI primitives (Radix), and smooth interactions (Framer Motion) to ship an inclusive, production-grade frontend experience.
- Automated build pipeline improvements (prebuild script to bump service worker version, optimized code-splitting) to reduce bundle size and improve perceived performance.
Technologies Used:
Project Links:
Bilingual conversational assistant powered by Google Gemini 2.5-Flash with RAG pipeline and WhatsApp escalation for solar energy company.
Key Responsibilities:
- Implemented a bilingual (PT/EN) conversational assistant powered by Google Gemini 2.5-Flash, with language detection and persistent context.
- Built a RAG pipeline + knowledge base and verification layers to minimize hallucinations and ensure company-data correctness.
- Implemented WhatsApp escalation for human handoff and quick-action flows for common requests; improved customer self-service by 25%.
- Production deployment: Vercel serverless functions, env-secure API integration, rate-limit planning, robust fallback/error handling, mobile-optimized UX (React + TypeScript + Framer Motion + Tailwind).
Technologies Used:
Project Links:
AI-driven medical platform providing symptom analysis and differential diagnosis with clinical-grade data sourcing.
Key Responsibilities:
- Integrated Isabel Healthcare API to power AI-driven symptom analysis and differential diagnosis, ensuring clinical-grade data sourcing.
- Architected serverless backend (AWS Lambda, API Gateway) with secure auth (Cognito) and production monitoring (CloudWatch), enabling reliable real-time interactions.
- Implemented frontend hosting and CI/CD via AWS Amplify and CloudFront for fast, globally distributed delivery.
- Built analytics dashboards and monitoring to track system health and performance (telemetry & logging).
Technologies Used:
Project Links:
Full-stack health & fitness platform with secure authentication, workout tracking, and interactive analytics dashboards.
Key Responsibilities:
- Built first full-stack health & fitness platform with secure authentication, workout tracking, and interactive analytics dashboards; established CI/CD pipelines (AWS Amplify, GitHub Actions) for rapid, reliable releases.
- Implemented realtime UX features (progress tracking and dashboards) and telemetry to measure performance and user flows.
- Led end-to-end development of a fitness app: product design → auth → real-time dashboards → CI/CD and deployments. This project passed by MLH Fellowship which validates its maturity.
Technologies Used:
Project Links:
Get In Touch
Have a project in mind, a question, or just want to connect? Feel free to reach out!
Contact Information
Alternatively, you can reach me through the following channels:
Preferred Contact Method:
Email is generally the quickest way to get a response for inquiries. For professional networking, LinkedIn is also a great option.