Explorar las categorías
Explora
Fiverr Pro
Español
$
USD
Marcos G
@theblueflash202
AI Engineer and Web Developer React n8n Python SEO
Estados Unidos
Español, Inglés
Sobre mí
I am an AI engineer and web developer with experience in n8n automation, React, Python, OpenAI API, RAG, and technical SEO/GEO. I build API integrations, custom forms connected to Google Sheets, OCR document-search tools, and responsive websites, including WordPress to Next.js/React migrations. My projects include a source-grounded RAG chatbot and a React/Firebase portfolio with real-time messaging and GitHub integration. I hold a B.S. in Information Science from USF. You receive tested work, source code, and clear documentation.
Habilidades
Marcos G
desconectado •
Revisa mis servicios
Sitios web personalizados
I will migrate wordpress to nextjs or react with SEO aeo and GEO
API e integraciones
I will build a custom web form connected to google sheets
Porfolio
Experiencia laboral
AI Engineering Intern
Apsis Solutions
May 2026 - Present • 4 mos
Build and deploy multistage n8n workflows for lead generation, outreach, content aggregation, and third-party API integrations. Develop website infrastructure and implement technical SEO and Generative Engine Optimization improvements, using analytics to evaluate search visibility.
Web Management Intern
BHM
May 2026 - Present • 4 mos
Part-time internship concurrent with Apsis Solutions. Rebuilt key landing pages in WordPress and Elementor; audited HTML and PageSpeed Insights JSON to identify plugin conflicts and improve load performance. Used Google Search Console and ZeroRank AI to identify content gaps and guide technical SEO and GEO improvements. Worked with the Marketing Director to translate analytics into website updates.
Administrative Assistant - Automation & Data Systems
University of South Florida
Aug 2024 - May 2026 • 1 yr 9 mos
Built a Python OCR retrieval system with pytesseract and pdfplumber to search PDF and DOCX archives by keyword and return the exact file path and page number, reducing staff document retrieval time by an estimated 60-80%. Added classification by detected document headings and reorganized legacy records to reduce duplicate searches. Partnered with institute staff to prioritize search needs, documented setup and usage, and trained staff for a sustainable handoff.
