About Me
AI-first Full-Stack Engineer — shipped production LLM agents & RAG systems (Google Gemini, Vercel/AWS). Deployed Google Gemini 1.5-Flash chat flows, serverless ML APIs, and CI/CD-hardened deployments (AWS, Vercel). Focused on verifiable, observable AI features and reducing hallucination through KB + verification layers.
My Expertise
Experience & Projects
LLM-powered agents and production prompt engineering with automated testing pipelines and serverless ML APIs.
Key Responsibilities:
- Built and fine-tuned LLM-powered agents (ChatGPT, Claude-Sonnet, Amazon Q) and production prompt engineering flows, improving output relevance and consistency.
- Designed AI-driven testing pipelines and automated test-case generation, increasing automated coverage and reducing manual QA cycles.
- Deployed a serverless ML churn-prediction API (Python, scikit-learn, AWS Lambda) with telemetry and automated evaluation for production monitoring.
Technologies Used:
Bilingual conversational assistant powered by Google Gemini 1.5-Flash with RAG pipeline and WhatsApp escalation for solar energy company.
Key Responsibilities:
- Implemented a bilingual (PT/EN) conversational assistant powered by Google Gemini 1.5-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.