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Backend Development Frontend Development JavaScript PHP Python
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Juan F.

@juanpablomacf

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5.0
4

3.3

3.3

100%

AI/ML/LLM/RAG & Automation AIVoice Chat | Web, n8n

$50 USD / Hour

・

Flag of

Chile (4:13 AM)

・

Joined on January 28, 2026

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1 Recommendation

$50 USD / Hour

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I transform complex business challenges into scalable AI solutions that deliver measurable results. With over a decade of experience in both full-stack development and AI implementation, I bridge the gap between ambitious ideas and production-ready systems. 🏆 Proven Impact Across Industries FinTech: Built trading dashboards processing 50,000+ daily transactions with real-time analytics MedTech: Developed AI diagnostic assistants that reduced analysis time by 65% LegalTech: Implemented RAG systems that cut legal research from hours to minutes SaaS: Scaled platforms from MVP to 100,000+ users with integrated AI capabilities 🔧 Technical Expertise AI & Machine Learning AI Agent Systems: Multi-step reasoning and workflow orchestration RAG Pipelines: LangChain, LlamaIndex, Pinecone, ChromaDB (95%+ retrieval accuracy) LLM Integrations: GPT-4, Claude 3, LLaMA fine-tuning and optimization Voice AI: Twilio integration and real-time call processing Full-Stack Development Frontend: React/Next.js, TypeScript Backend: Node.js, Python, FastAPI DevOps: AWS, Docker, Kubernetes, CI/CD pipelines Automation: n8n workflows, custom API integrations 🚀 Recent Deliverables • AI Customer Support: Reduced ticket volume by 75% with bots handling 15,000+ monthly conversations • Document Intelligence: Built legal document analysis that cut review time from 4 hours to 15 minutes • Trading Analytics: Delivered real-time dashboards with 99.9% uptime for financial clients • Workflow Automation: Saved 200+ manual hours monthly through n8n-powered processes 🎯 My Approach Strategy & Planning Technical feasibility analysis and ROI-focused project scoping Scalable architecture design for long-term growth Execution & Delivery AI-enhanced development using Cursor and Copilot Agile methodology with transparent weekly progress updates Comprehensive testing and quality assurance Production Excellence Robust monitoring, logging, and error handling Performance optimization and thorough documentation 📈 Why Choose Senior Expertise? I architect systems that scale, implementing proper error handling, security protocols, and maintainable codebases. My clients avoid technical debt while accelerating their AI roadmap with production-ready solutions. I'm available for full-time engagements and ready to discuss how I can help bring your AI vision to life.

Verifications

On time

100%

On budget

100%

Accept rate

90%

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Portfolio

Portfolio

13793829
Architected and developed a full-stack platform for buying, selling, and managing fine wine as an asset class. The system solved complex problems unique to alternative assets: **provenance tracking** (chain-of-custody recorded on a private blockchain ledger for high-value lots), **condition grading** (users submitted cellar photos analyzed by computer vision to suggest storage quality), and **dynamic valuation** (integrating auction API data, critic scores, and market demand signals). The marketplace backend (Node.js, Postgres) handled bid/ask order matching and escrow services. The core for users was the "Digital Cellar" – a React frontend allowing collectors to catalog bottles, view estimated portfolio value over time, and get AI-driven selling recommendations ("Drink, Hold, or Sell") based on peak maturity windows. A standout B2B feature was the "Trade Liquidity Pool" API for wine merchants, enabling them to programmatically list and source inventory. T

Fine Wine Marketplace & Portfolio

Architected and developed a full-stack platform for buying, selling, and managing fine wine as an asset class. The system solved complex problems unique to alternative assets: **provenance tracking** (chain-of-custody recorded on a private blockchain ledger for high-value lots), **condition grading** (users submitted cellar photos analyzed by computer vision to suggest storage quality), and **dynamic valuation** (integrating auction API data, critic scores, and market demand signals). The marketplace backend (Node.js, Postgres) handled bid/ask order matching and escrow services. The core for users was the "Digital Cellar" – a React frontend allowing collectors to catalog bottles, view estimated portfolio value over time, and get AI-driven selling recommendations ("Drink, Hold, or Sell") based on peak maturity windows. A standout B2B feature was the "Trade Liquidity Pool" API for wine merchants, enabling them to programmatically list and source inventory. T

Fine Wine Marketplace & Portfolio

Architected and developed a full-stack platform for buying, selling, and managing fine wine as an asset class. The system solved complex problems unique to alternative assets: **provenance tracking** (chain-of-custody recorded on a private blockchain ledger for high-value lots), **condition grading** (users submitted cellar photos analyzed by computer vision to suggest storage quality), and **dynamic valuation** (integrating auction API data, critic scores, and market demand signals). The marketplace backend (Node.js, Postgres) handled bid/ask order matching and escrow services. The core for users was the "Digital Cellar" – a React frontend allowing collectors to catalog bottles, view estimated portfolio value over time, and get AI-driven selling recommendations ("Drink, Hold, or Sell") based on peak maturity windows. A standout B2B feature was the "Trade Liquidity Pool" API for wine merchants, enabling them to programmatically list and source inventory. T

Fine Wine Marketplace & Portfolio

13793819
Designed and developed a comprehensive health information and wellness tracking platform, modeled on the editorial rigor of Verywell Health. The core was a custom headless CMS (built with Strapi) that enforced a strict editorial workflow: writers submitted drafts, which were assigned to medical reviewers (doctors, nurses) via an integrated task system, with version control and change tracking for compliance. Published content was richly structured, with separate fields for summary, key takeaways, evidence ratings, and citations linked to PubMed IDs. The frontend (Next.js, TypeScript) presented this with exceptional readability: a dynamic table of contents, interactive "explainers" for complex terms, and a print-optimized view. A companion "My Wellness" section allowed users to privately track symptoms, medications, and appointments, with data visualizations (Recharts) to identify trends. A key technical challenge was building a real-time "Health News & Reca

Medical-Review Health Content

Designed and developed a comprehensive health information and wellness tracking platform, modeled on the editorial rigor of Verywell Health. The core was a custom headless CMS (built with Strapi) that enforced a strict editorial workflow: writers submitted drafts, which were assigned to medical reviewers (doctors, nurses) via an integrated task system, with version control and change tracking for compliance. Published content was richly structured, with separate fields for summary, key takeaways, evidence ratings, and citations linked to PubMed IDs. The frontend (Next.js, TypeScript) presented this with exceptional readability: a dynamic table of contents, interactive "explainers" for complex terms, and a print-optimized view. A companion "My Wellness" section allowed users to privately track symptoms, medications, and appointments, with data visualizations (Recharts) to identify trends. A key technical challenge was building a real-time "Health News & Reca

Medical-Review Health Content

Designed and developed a comprehensive health information and wellness tracking platform, modeled on the editorial rigor of Verywell Health. The core was a custom headless CMS (built with Strapi) that enforced a strict editorial workflow: writers submitted drafts, which were assigned to medical reviewers (doctors, nurses) via an integrated task system, with version control and change tracking for compliance. Published content was richly structured, with separate fields for summary, key takeaways, evidence ratings, and citations linked to PubMed IDs. The frontend (Next.js, TypeScript) presented this with exceptional readability: a dynamic table of contents, interactive "explainers" for complex terms, and a print-optimized view. A companion "My Wellness" section allowed users to privately track symptoms, medications, and appointments, with data visualizations (Recharts) to identify trends. A key technical challenge was building a real-time "Health News & Reca

Medical-Review Health Content

Designed and developed a comprehensive health information and wellness tracking platform, modeled on the editorial rigor of Verywell Health. The core was a custom headless CMS (built with Strapi) that enforced a strict editorial workflow: writers submitted drafts, which were assigned to medical reviewers (doctors, nurses) via an integrated task system, with version control and change tracking for compliance. Published content was richly structured, with separate fields for summary, key takeaways, evidence ratings, and citations linked to PubMed IDs. The frontend (Next.js, TypeScript) presented this with exceptional readability: a dynamic table of contents, interactive "explainers" for complex terms, and a print-optimized view. A companion "My Wellness" section allowed users to privately track symptoms, medications, and appointments, with data visualizations (Recharts) to identify trends. A key technical challenge was building a real-time "Health News & Reca

Medical-Review Health Content

13793810
Architected and led development of a next-generation luxury fashion e-commerce platform for a global brand. The project involved migrating from a legacy monolith to a headless commerce architecture. The backend comprised microservices (Node.js/TypeScript, gRPC) for cart/checkout, inventory (integrating with SAP), and a product information management (PIM) system handling complex variant logic (colors, sizes, materials). The frontend was a performant React/Next.js application with a focus on visual storytelling: high-resolution image zoom, 360° product views (using WebGL/Three.js), and video lookbooks. A core feature was the "Digital Style Guide" – an interactive outfit builder that used a graph database (Neo4j) to suggest complementary items based on style rules, seasonality, and live inventory. The platform featured deep personalization, integrating with a CDP to serve dynamic content based on customer tier (e.g., Ralph Lauren Purple Label customers saw exclusive products).

Luxury Fashion E-commerce & Styling

Architected and led development of a next-generation luxury fashion e-commerce platform for a global brand. The project involved migrating from a legacy monolith to a headless commerce architecture. The backend comprised microservices (Node.js/TypeScript, gRPC) for cart/checkout, inventory (integrating with SAP), and a product information management (PIM) system handling complex variant logic (colors, sizes, materials). The frontend was a performant React/Next.js application with a focus on visual storytelling: high-resolution image zoom, 360° product views (using WebGL/Three.js), and video lookbooks. A core feature was the "Digital Style Guide" – an interactive outfit builder that used a graph database (Neo4j) to suggest complementary items based on style rules, seasonality, and live inventory. The platform featured deep personalization, integrating with a CDP to serve dynamic content based on customer tier (e.g., Ralph Lauren Purple Label customers saw exclusive products).

Luxury Fashion E-commerce & Styling

Architected and led development of a next-generation luxury fashion e-commerce platform for a global brand. The project involved migrating from a legacy monolith to a headless commerce architecture. The backend comprised microservices (Node.js/TypeScript, gRPC) for cart/checkout, inventory (integrating with SAP), and a product information management (PIM) system handling complex variant logic (colors, sizes, materials). The frontend was a performant React/Next.js application with a focus on visual storytelling: high-resolution image zoom, 360° product views (using WebGL/Three.js), and video lookbooks. A core feature was the "Digital Style Guide" – an interactive outfit builder that used a graph database (Neo4j) to suggest complementary items based on style rules, seasonality, and live inventory. The platform featured deep personalization, integrating with a CDP to serve dynamic content based on customer tier (e.g., Ralph Lauren Purple Label customers saw exclusive products).

Luxury Fashion E-commerce & Styling

Architected and led development of a next-generation luxury fashion e-commerce platform for a global brand. The project involved migrating from a legacy monolith to a headless commerce architecture. The backend comprised microservices (Node.js/TypeScript, gRPC) for cart/checkout, inventory (integrating with SAP), and a product information management (PIM) system handling complex variant logic (colors, sizes, materials). The frontend was a performant React/Next.js application with a focus on visual storytelling: high-resolution image zoom, 360° product views (using WebGL/Three.js), and video lookbooks. A core feature was the "Digital Style Guide" – an interactive outfit builder that used a graph database (Neo4j) to suggest complementary items based on style rules, seasonality, and live inventory. The platform featured deep personalization, integrating with a CDP to serve dynamic content based on customer tier (e.g., Ralph Lauren Purple Label customers saw exclusive products).

Luxury Fashion E-commerce & Styling

13793807
esigned and developed a full-stack health information and moderated community platform, inspired by Patient.info, with a focus on safety and evidence-based content. The platform featured two core systems: 1) A guided symptom checker that used a decision-tree engine (stored as a directed graph in Neo4j) to provide users with possible condition information and advised next steps (self-care, pharmacy, GP, A&E), clearly citing NHS and NICE guidelines. 2) A patient community forum with robust moderation tools. All user-generated content (posts, symptoms) passed through a real-time NLP moderation layer (using spaCy and custom classifiers) to flag personal health information (PHI) for redaction and identify high-risk content (e.g., suicide ideation) for immediate human review. The backend (Python/Django) enforced strict data segregation and provided anonymized data exports for public health trend analysis. The React/Next.js frontend was designed for accessibility (WCAG 2.1 AA) and low hea

Symptom Checker & Patient Support

esigned and developed a full-stack health information and moderated community platform, inspired by Patient.info, with a focus on safety and evidence-based content. The platform featured two core systems: 1) A guided symptom checker that used a decision-tree engine (stored as a directed graph in Neo4j) to provide users with possible condition information and advised next steps (self-care, pharmacy, GP, A&E), clearly citing NHS and NICE guidelines. 2) A patient community forum with robust moderation tools. All user-generated content (posts, symptoms) passed through a real-time NLP moderation layer (using spaCy and custom classifiers) to flag personal health information (PHI) for redaction and identify high-risk content (e.g., suicide ideation) for immediate human review. The backend (Python/Django) enforced strict data segregation and provided anonymized data exports for public health trend analysis. The React/Next.js frontend was designed for accessibility (WCAG 2.1 AA) and low hea

Symptom Checker & Patient Support

esigned and developed a full-stack health information and moderated community platform, inspired by Patient.info, with a focus on safety and evidence-based content. The platform featured two core systems: 1) A guided symptom checker that used a decision-tree engine (stored as a directed graph in Neo4j) to provide users with possible condition information and advised next steps (self-care, pharmacy, GP, A&E), clearly citing NHS and NICE guidelines. 2) A patient community forum with robust moderation tools. All user-generated content (posts, symptoms) passed through a real-time NLP moderation layer (using spaCy and custom classifiers) to flag personal health information (PHI) for redaction and identify high-risk content (e.g., suicide ideation) for immediate human review. The backend (Python/Django) enforced strict data segregation and provided anonymized data exports for public health trend analysis. The React/Next.js frontend was designed for accessibility (WCAG 2.1 AA) and low hea

Symptom Checker & Patient Support

13793802
Architected and developed a full-stack platform for PC enthusiasts to build custom systems and track hardware prices across retailers like Newegg, Amazon, and Microcenter. The system featured a high-frequency data pipeline that used a combination of retailer APIs and robust, rate-limited browser automation (Playwright) to monitor prices, inventory status, and promo codes for over 500,000 SKUs in near real-time. Data was normalized, deduplicated, and stored in a time-series database (TimescaleDB) for price history analysis. The core application was an interactive PC Builder: a React frontend with a drag-and-drop interface and a GraphQL backend (Apollo Server) that enforced hardware compatibility rules (socket types, wattage, form factors) via a product ontology. A key feature was the "Price Alert & Build Watch" system, where users could save builds and receive notifications (email, WebSocket) when total cost dropped below a threshold or compatibility-impacting parts went o

PC Builder & Hardware Price Tracking

Architected and developed a full-stack platform for PC enthusiasts to build custom systems and track hardware prices across retailers like Newegg, Amazon, and Microcenter. The system featured a high-frequency data pipeline that used a combination of retailer APIs and robust, rate-limited browser automation (Playwright) to monitor prices, inventory status, and promo codes for over 500,000 SKUs in near real-time. Data was normalized, deduplicated, and stored in a time-series database (TimescaleDB) for price history analysis. The core application was an interactive PC Builder: a React frontend with a drag-and-drop interface and a GraphQL backend (Apollo Server) that enforced hardware compatibility rules (socket types, wattage, form factors) via a product ontology. A key feature was the "Price Alert & Build Watch" system, where users could save builds and receive notifications (email, WebSocket) when total cost dropped below a threshold or compatibility-impacting parts went o

PC Builder & Hardware Price Tracking

Architected and developed a full-stack platform for PC enthusiasts to build custom systems and track hardware prices across retailers like Newegg, Amazon, and Microcenter. The system featured a high-frequency data pipeline that used a combination of retailer APIs and robust, rate-limited browser automation (Playwright) to monitor prices, inventory status, and promo codes for over 500,000 SKUs in near real-time. Data was normalized, deduplicated, and stored in a time-series database (TimescaleDB) for price history analysis. The core application was an interactive PC Builder: a React frontend with a drag-and-drop interface and a GraphQL backend (Apollo Server) that enforced hardware compatibility rules (socket types, wattage, form factors) via a product ontology. A key feature was the "Price Alert & Build Watch" system, where users could save builds and receive notifications (email, WebSocket) when total cost dropped below a threshold or compatibility-impacting parts went o

PC Builder & Hardware Price Tracking

Architected and developed a full-stack platform for PC enthusiasts to build custom systems and track hardware prices across retailers like Newegg, Amazon, and Microcenter. The system featured a high-frequency data pipeline that used a combination of retailer APIs and robust, rate-limited browser automation (Playwright) to monitor prices, inventory status, and promo codes for over 500,000 SKUs in near real-time. Data was normalized, deduplicated, and stored in a time-series database (TimescaleDB) for price history analysis. The core application was an interactive PC Builder: a React frontend with a drag-and-drop interface and a GraphQL backend (Apollo Server) that enforced hardware compatibility rules (socket types, wattage, form factors) via a product ontology. A key feature was the "Price Alert & Build Watch" system, where users could save builds and receive notifications (email, WebSocket) when total cost dropped below a threshold or compatibility-impacting parts went o

PC Builder & Hardware Price Tracking

13793797
Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

13793829
Architected and developed a full-stack platform for buying, selling, and managing fine wine as an asset class. The system solved complex problems unique to alternative assets: **provenance tracking** (chain-of-custody recorded on a private blockchain ledger for high-value lots), **condition grading** (users submitted cellar photos analyzed by computer vision to suggest storage quality), and **dynamic valuation** (integrating auction API data, critic scores, and market demand signals). The marketplace backend (Node.js, Postgres) handled bid/ask order matching and escrow services. The core for users was the "Digital Cellar" – a React frontend allowing collectors to catalog bottles, view estimated portfolio value over time, and get AI-driven selling recommendations ("Drink, Hold, or Sell") based on peak maturity windows. A standout B2B feature was the "Trade Liquidity Pool" API for wine merchants, enabling them to programmatically list and source inventory. T

Fine Wine Marketplace & Portfolio

Architected and developed a full-stack platform for buying, selling, and managing fine wine as an asset class. The system solved complex problems unique to alternative assets: **provenance tracking** (chain-of-custody recorded on a private blockchain ledger for high-value lots), **condition grading** (users submitted cellar photos analyzed by computer vision to suggest storage quality), and **dynamic valuation** (integrating auction API data, critic scores, and market demand signals). The marketplace backend (Node.js, Postgres) handled bid/ask order matching and escrow services. The core for users was the "Digital Cellar" – a React frontend allowing collectors to catalog bottles, view estimated portfolio value over time, and get AI-driven selling recommendations ("Drink, Hold, or Sell") based on peak maturity windows. A standout B2B feature was the "Trade Liquidity Pool" API for wine merchants, enabling them to programmatically list and source inventory. T

Fine Wine Marketplace & Portfolio

Architected and developed a full-stack platform for buying, selling, and managing fine wine as an asset class. The system solved complex problems unique to alternative assets: **provenance tracking** (chain-of-custody recorded on a private blockchain ledger for high-value lots), **condition grading** (users submitted cellar photos analyzed by computer vision to suggest storage quality), and **dynamic valuation** (integrating auction API data, critic scores, and market demand signals). The marketplace backend (Node.js, Postgres) handled bid/ask order matching and escrow services. The core for users was the "Digital Cellar" – a React frontend allowing collectors to catalog bottles, view estimated portfolio value over time, and get AI-driven selling recommendations ("Drink, Hold, or Sell") based on peak maturity windows. A standout B2B feature was the "Trade Liquidity Pool" API for wine merchants, enabling them to programmatically list and source inventory. T

Fine Wine Marketplace & Portfolio

13793819
Designed and developed a comprehensive health information and wellness tracking platform, modeled on the editorial rigor of Verywell Health. The core was a custom headless CMS (built with Strapi) that enforced a strict editorial workflow: writers submitted drafts, which were assigned to medical reviewers (doctors, nurses) via an integrated task system, with version control and change tracking for compliance. Published content was richly structured, with separate fields for summary, key takeaways, evidence ratings, and citations linked to PubMed IDs. The frontend (Next.js, TypeScript) presented this with exceptional readability: a dynamic table of contents, interactive "explainers" for complex terms, and a print-optimized view. A companion "My Wellness" section allowed users to privately track symptoms, medications, and appointments, with data visualizations (Recharts) to identify trends. A key technical challenge was building a real-time "Health News & Reca

Medical-Review Health Content

Designed and developed a comprehensive health information and wellness tracking platform, modeled on the editorial rigor of Verywell Health. The core was a custom headless CMS (built with Strapi) that enforced a strict editorial workflow: writers submitted drafts, which were assigned to medical reviewers (doctors, nurses) via an integrated task system, with version control and change tracking for compliance. Published content was richly structured, with separate fields for summary, key takeaways, evidence ratings, and citations linked to PubMed IDs. The frontend (Next.js, TypeScript) presented this with exceptional readability: a dynamic table of contents, interactive "explainers" for complex terms, and a print-optimized view. A companion "My Wellness" section allowed users to privately track symptoms, medications, and appointments, with data visualizations (Recharts) to identify trends. A key technical challenge was building a real-time "Health News & Reca

Medical-Review Health Content

Designed and developed a comprehensive health information and wellness tracking platform, modeled on the editorial rigor of Verywell Health. The core was a custom headless CMS (built with Strapi) that enforced a strict editorial workflow: writers submitted drafts, which were assigned to medical reviewers (doctors, nurses) via an integrated task system, with version control and change tracking for compliance. Published content was richly structured, with separate fields for summary, key takeaways, evidence ratings, and citations linked to PubMed IDs. The frontend (Next.js, TypeScript) presented this with exceptional readability: a dynamic table of contents, interactive "explainers" for complex terms, and a print-optimized view. A companion "My Wellness" section allowed users to privately track symptoms, medications, and appointments, with data visualizations (Recharts) to identify trends. A key technical challenge was building a real-time "Health News & Reca

Medical-Review Health Content

Designed and developed a comprehensive health information and wellness tracking platform, modeled on the editorial rigor of Verywell Health. The core was a custom headless CMS (built with Strapi) that enforced a strict editorial workflow: writers submitted drafts, which were assigned to medical reviewers (doctors, nurses) via an integrated task system, with version control and change tracking for compliance. Published content was richly structured, with separate fields for summary, key takeaways, evidence ratings, and citations linked to PubMed IDs. The frontend (Next.js, TypeScript) presented this with exceptional readability: a dynamic table of contents, interactive "explainers" for complex terms, and a print-optimized view. A companion "My Wellness" section allowed users to privately track symptoms, medications, and appointments, with data visualizations (Recharts) to identify trends. A key technical challenge was building a real-time "Health News & Reca

Medical-Review Health Content

13793810
Architected and led development of a next-generation luxury fashion e-commerce platform for a global brand. The project involved migrating from a legacy monolith to a headless commerce architecture. The backend comprised microservices (Node.js/TypeScript, gRPC) for cart/checkout, inventory (integrating with SAP), and a product information management (PIM) system handling complex variant logic (colors, sizes, materials). The frontend was a performant React/Next.js application with a focus on visual storytelling: high-resolution image zoom, 360° product views (using WebGL/Three.js), and video lookbooks. A core feature was the "Digital Style Guide" – an interactive outfit builder that used a graph database (Neo4j) to suggest complementary items based on style rules, seasonality, and live inventory. The platform featured deep personalization, integrating with a CDP to serve dynamic content based on customer tier (e.g., Ralph Lauren Purple Label customers saw exclusive products).

Luxury Fashion E-commerce & Styling

Architected and led development of a next-generation luxury fashion e-commerce platform for a global brand. The project involved migrating from a legacy monolith to a headless commerce architecture. The backend comprised microservices (Node.js/TypeScript, gRPC) for cart/checkout, inventory (integrating with SAP), and a product information management (PIM) system handling complex variant logic (colors, sizes, materials). The frontend was a performant React/Next.js application with a focus on visual storytelling: high-resolution image zoom, 360° product views (using WebGL/Three.js), and video lookbooks. A core feature was the "Digital Style Guide" – an interactive outfit builder that used a graph database (Neo4j) to suggest complementary items based on style rules, seasonality, and live inventory. The platform featured deep personalization, integrating with a CDP to serve dynamic content based on customer tier (e.g., Ralph Lauren Purple Label customers saw exclusive products).

Luxury Fashion E-commerce & Styling

Architected and led development of a next-generation luxury fashion e-commerce platform for a global brand. The project involved migrating from a legacy monolith to a headless commerce architecture. The backend comprised microservices (Node.js/TypeScript, gRPC) for cart/checkout, inventory (integrating with SAP), and a product information management (PIM) system handling complex variant logic (colors, sizes, materials). The frontend was a performant React/Next.js application with a focus on visual storytelling: high-resolution image zoom, 360° product views (using WebGL/Three.js), and video lookbooks. A core feature was the "Digital Style Guide" – an interactive outfit builder that used a graph database (Neo4j) to suggest complementary items based on style rules, seasonality, and live inventory. The platform featured deep personalization, integrating with a CDP to serve dynamic content based on customer tier (e.g., Ralph Lauren Purple Label customers saw exclusive products).

Luxury Fashion E-commerce & Styling

Architected and led development of a next-generation luxury fashion e-commerce platform for a global brand. The project involved migrating from a legacy monolith to a headless commerce architecture. The backend comprised microservices (Node.js/TypeScript, gRPC) for cart/checkout, inventory (integrating with SAP), and a product information management (PIM) system handling complex variant logic (colors, sizes, materials). The frontend was a performant React/Next.js application with a focus on visual storytelling: high-resolution image zoom, 360° product views (using WebGL/Three.js), and video lookbooks. A core feature was the "Digital Style Guide" – an interactive outfit builder that used a graph database (Neo4j) to suggest complementary items based on style rules, seasonality, and live inventory. The platform featured deep personalization, integrating with a CDP to serve dynamic content based on customer tier (e.g., Ralph Lauren Purple Label customers saw exclusive products).

Luxury Fashion E-commerce & Styling

13793807
esigned and developed a full-stack health information and moderated community platform, inspired by Patient.info, with a focus on safety and evidence-based content. The platform featured two core systems: 1) A guided symptom checker that used a decision-tree engine (stored as a directed graph in Neo4j) to provide users with possible condition information and advised next steps (self-care, pharmacy, GP, A&E), clearly citing NHS and NICE guidelines. 2) A patient community forum with robust moderation tools. All user-generated content (posts, symptoms) passed through a real-time NLP moderation layer (using spaCy and custom classifiers) to flag personal health information (PHI) for redaction and identify high-risk content (e.g., suicide ideation) for immediate human review. The backend (Python/Django) enforced strict data segregation and provided anonymized data exports for public health trend analysis. The React/Next.js frontend was designed for accessibility (WCAG 2.1 AA) and low hea

Symptom Checker & Patient Support

esigned and developed a full-stack health information and moderated community platform, inspired by Patient.info, with a focus on safety and evidence-based content. The platform featured two core systems: 1) A guided symptom checker that used a decision-tree engine (stored as a directed graph in Neo4j) to provide users with possible condition information and advised next steps (self-care, pharmacy, GP, A&E), clearly citing NHS and NICE guidelines. 2) A patient community forum with robust moderation tools. All user-generated content (posts, symptoms) passed through a real-time NLP moderation layer (using spaCy and custom classifiers) to flag personal health information (PHI) for redaction and identify high-risk content (e.g., suicide ideation) for immediate human review. The backend (Python/Django) enforced strict data segregation and provided anonymized data exports for public health trend analysis. The React/Next.js frontend was designed for accessibility (WCAG 2.1 AA) and low hea

Symptom Checker & Patient Support

esigned and developed a full-stack health information and moderated community platform, inspired by Patient.info, with a focus on safety and evidence-based content. The platform featured two core systems: 1) A guided symptom checker that used a decision-tree engine (stored as a directed graph in Neo4j) to provide users with possible condition information and advised next steps (self-care, pharmacy, GP, A&E), clearly citing NHS and NICE guidelines. 2) A patient community forum with robust moderation tools. All user-generated content (posts, symptoms) passed through a real-time NLP moderation layer (using spaCy and custom classifiers) to flag personal health information (PHI) for redaction and identify high-risk content (e.g., suicide ideation) for immediate human review. The backend (Python/Django) enforced strict data segregation and provided anonymized data exports for public health trend analysis. The React/Next.js frontend was designed for accessibility (WCAG 2.1 AA) and low hea

Symptom Checker & Patient Support

13793802
Architected and developed a full-stack platform for PC enthusiasts to build custom systems and track hardware prices across retailers like Newegg, Amazon, and Microcenter. The system featured a high-frequency data pipeline that used a combination of retailer APIs and robust, rate-limited browser automation (Playwright) to monitor prices, inventory status, and promo codes for over 500,000 SKUs in near real-time. Data was normalized, deduplicated, and stored in a time-series database (TimescaleDB) for price history analysis. The core application was an interactive PC Builder: a React frontend with a drag-and-drop interface and a GraphQL backend (Apollo Server) that enforced hardware compatibility rules (socket types, wattage, form factors) via a product ontology. A key feature was the "Price Alert & Build Watch" system, where users could save builds and receive notifications (email, WebSocket) when total cost dropped below a threshold or compatibility-impacting parts went o

PC Builder & Hardware Price Tracking

Architected and developed a full-stack platform for PC enthusiasts to build custom systems and track hardware prices across retailers like Newegg, Amazon, and Microcenter. The system featured a high-frequency data pipeline that used a combination of retailer APIs and robust, rate-limited browser automation (Playwright) to monitor prices, inventory status, and promo codes for over 500,000 SKUs in near real-time. Data was normalized, deduplicated, and stored in a time-series database (TimescaleDB) for price history analysis. The core application was an interactive PC Builder: a React frontend with a drag-and-drop interface and a GraphQL backend (Apollo Server) that enforced hardware compatibility rules (socket types, wattage, form factors) via a product ontology. A key feature was the "Price Alert & Build Watch" system, where users could save builds and receive notifications (email, WebSocket) when total cost dropped below a threshold or compatibility-impacting parts went o

PC Builder & Hardware Price Tracking

Architected and developed a full-stack platform for PC enthusiasts to build custom systems and track hardware prices across retailers like Newegg, Amazon, and Microcenter. The system featured a high-frequency data pipeline that used a combination of retailer APIs and robust, rate-limited browser automation (Playwright) to monitor prices, inventory status, and promo codes for over 500,000 SKUs in near real-time. Data was normalized, deduplicated, and stored in a time-series database (TimescaleDB) for price history analysis. The core application was an interactive PC Builder: a React frontend with a drag-and-drop interface and a GraphQL backend (Apollo Server) that enforced hardware compatibility rules (socket types, wattage, form factors) via a product ontology. A key feature was the "Price Alert & Build Watch" system, where users could save builds and receive notifications (email, WebSocket) when total cost dropped below a threshold or compatibility-impacting parts went o

PC Builder & Hardware Price Tracking

Architected and developed a full-stack platform for PC enthusiasts to build custom systems and track hardware prices across retailers like Newegg, Amazon, and Microcenter. The system featured a high-frequency data pipeline that used a combination of retailer APIs and robust, rate-limited browser automation (Playwright) to monitor prices, inventory status, and promo codes for over 500,000 SKUs in near real-time. Data was normalized, deduplicated, and stored in a time-series database (TimescaleDB) for price history analysis. The core application was an interactive PC Builder: a React frontend with a drag-and-drop interface and a GraphQL backend (Apollo Server) that enforced hardware compatibility rules (socket types, wattage, form factors) via a product ontology. A key feature was the "Price Alert & Build Watch" system, where users could save builds and receive notifications (email, WebSocket) when total cost dropped below a threshold or compatibility-impacting parts went o

PC Builder & Hardware Price Tracking

13793797
Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

Architected and developed a full-stack platform for discovering and booking luxury boutique hotels and experiences, inspired by the curated ethos of Mr & Mrs Smith. The project involved creating a sophisticated content management system (Headless WordPress/Strapi) for editors to craft rich narrative profiles for each property, complete with professional photography, video, and local experience guides. The booking engine was a microservice (Node.js, TypeScript) integrating multiple hotel supplier APIs (Sabre, Expedia Partner) with a unified caching and availability layer to ensure real-time rates. The core differentiator was the "Taste Profile" quiz—an interactive onboarding flow (React, Framer Motion) that used a decision-tree algorithm to segment users into traveler archetypes (e.g., "Cultural Purist," "Discreet Hedonist"). This profile powered a personalized homepage and email newsletter. The frontend (Next.js 14, App Router) was a performant, image-

Luxury Hotel Curation & Itinerary Pl

5.0 · 4 Reviews
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Servimediacion C.

5.0

€1,500 EUR

8 minutes ago

osticket Voicebot

Hemos desarrollado un proyecto grande y ha sido todo perfecto. Los conocimientos técnicos de Juan son muy amplios y la comunicación ha sido fluida , con consejos y todo bien organizado. Recomendado al 100%

JavaScript
Python
Software Architecture
Google App Engine
Voice Assistance Devices

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Fay C.

5.0

$120 USD

2 months ago

Help with Setup AI Assistant for MS Teams

He has done a good job. he is very honest person. he knows a lot about AI and setup

Automation
AI Text-to-text
AI Chatbot Development
AI Content Creation
AI Content Writing

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Ciancoders

5.0

$100 USD

2 months ago

Filtros Dinámicos para Reporte Django

todo muy bien con este freelancer recomendado

JavaScript
Python
Django
AngularJS
Backend Development

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Marisol C.

5.0

$40 USD

2 months ago

Proyecto SGI Geoespacial con Python

Saludos cordiales desde Ecuador. Juan es un excelente profesional; me brindó apoyo inmediato y demostró un alto nivel de compromiso desde el primer momento. Su trabajo destaca por la calidad, precisión y responsabilidad con la que cumple cada tarea. Es un profesional íntegro, con gran capacidad técnica y comunicación efectiva. Sin duda volvería a trabajar con él, ya que ofrece un servicio confiable y garantiza resultados. Lo recomiendo al 100%.

Python
Data Processing
Software Architecture
Cartography & Maps
Remote Sensing

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Youdsua M.

5.0

$200 USD

3 months ago

Sistema Web Expediente Dental

Excelente comunicación, tiempo dedicado a dar respuestas y explicaciones. Doy fe de que el proyecto se realizó de manera solicitada y aún mejor. Satisfecho al 100% con Juan Pablo y su experiencia.

PHP
Python
Django
NoSQL Couch & Mongo
Web Development

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