You will get MCP tools and AI agents integrated into your stack in 5 days
Rising Talent
Rising Talent
Project details
I build production-grade MCP integrations that turn AI agents into powerful workflow engines. Unlike generic freelancers, I bring deep infrastructure expertise from Rainfall - a backend API platform with 200+ integrated tools and workflows.
What you get:
✓ Clean, maintainable code with proper error handling & retry logic
✓ Production-ready authentication (OAuth, API keys, custom flows)
✓ Real-world experience with complex integrations across SaaS platforms
✓ Fast delivery without cutting corners
I specialize in connecting AI assistants to the tools your business actually uses - whether that's a single API integration or orchestrating multiple services into seamless workflows. Every project includes comprehensive documentation so you own the solution, not just the code.
Perfect for teams who want their AI agents to actually *do* things, not just chat about them.
What you get:
✓ Clean, maintainable code with proper error handling & retry logic
✓ Production-ready authentication (OAuth, API keys, custom flows)
✓ Real-world experience with complex integrations across SaaS platforms
✓ Fast delivery without cutting corners
I specialize in connecting AI assistants to the tools your business actually uses - whether that's a single API integration or orchestrating multiple services into seamless workflows. Every project includes comprehensive documentation so you own the solution, not just the code.
Perfect for teams who want their AI agents to actually *do* things, not just chat about them.
AI Algorithms
Large Language Model, Multimodal Large Language ModelAI Applications
AI Chatbot, AI Text-to-Image, AI Text-to-Speech, AI-Generated Code, Image RecognitionAI Development Language
PythonAI Tools
Hugging FaceAI Models
ChatGPT, LLaMAWhat's included
| Service Tiers |
Starter
$750
|
Standard
$2,500
|
Advanced
$8,000
|
|---|---|---|---|
| Delivery Time | 3 days | 10 days | 28 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
About Sekeol
AI Full-Stack Engineer | LLM Fine-Tuning | Rainfall API (200+ tools)
Santa Clara, United States - 11:29 pm local time
That architecture is more than a showpiece. It's the backbone of two completed live products (Harmonic: a booking/scheduling SaaS; Rainfall-Devkit: subscription based mcp/sdk access to the same backend that I use) and several in progress (draft-build AEC/MEP, personal workflow automation); it's the reason I can pick up most MCP/agent integration contracts in days, not weeks.
What I actually do:
• AI infrastructure & agent orchestration — RAG pipelines, MCP integrations, multi-tool workflow systems
• LLM fine-tuning — LoRA, ORPO, SFT on 36B–120B models (Hugging Face: the-fall-of-man; Nightbloom 36B, Didact 117B series)
• Full-stack delivery: Next.js + Bun + PostgreSQL/Redis; I ship, I don't prototype
• Booking & scheduling systems: Groupon Booking Architect (4+ years), Harmonic (live, soft-launched)
Enterprise background: Principal Engineer @ Groupon (4.5 years, third-party booking at scale), VP Engineering @ Palm Finance (15x infrastructure cost reduction via distributed cloudless architecture, 50M+ record AI-indexed data warehouse).
I work in TypeScript/JavaScript (Bun-first), Python, Rust, and Ruby. I run a tight monorepo, write real tests, and don't cut corners that come back as incidents.
Available for: MCP integration sprints, AI workflow design & build, LLM fine-tuning audits, booking/scheduling system builds, full-stack AI SaaS contracts.
Steps for completing your project
After purchasing the project, send requirements so Sekeol can start the project.
Delivery time starts when Sekeol receives requirements from you.
Sekeol works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & Architecture Planning
Review your requirements, map out the integration architecture, and confirm the approach before writing code.
Implementation & Integration
Build the MCP tools with proper error handling, authentication, and testing. You'll get updates as progress is made.