I design and build intelligent, scalable AI systems that solve real-world problems using modern software architecture, cloud infrastructure, and cutting-edge machine learning.
Specializing in:
- Generative AI & LLM Applications
- Retrieval-Augmented Generation (RAG) Systems
- Multi-Agent AI Workflows & Orchestration
- Scalable Backend & Cloud-Native Architectures
I’m an AI & Software Engineer passionate about transforming ideas into intelligent, data-driven solutions.
My work sits at the intersection of AI research and software engineering, where I design and deploy production-ready systems powered by machine learning, cloud technologies, and modern backend architecture.
I enjoy:
- Architecting scalable AI platforms
- Designing data pipelines and vector retrieval systems
- Building multi-agent workflows
- Deploying real-time AI applications in the cloud
I’m continuously learning, building, and experimenting — from fine-tuning LLMs to architecting full-stack AI systems that make real impact.
- Python, PyTorch, TensorFlow
- Transformers, CNNs, NLP, Computer Vision
- LangChain, LangGraph, spaCy
- RAG Systems & LLM Application Design
- FastAPI, Flask, Spring Boot, Java
- REST APIs & Microservices Architecture
- Event-Driven Systems & Distributed Design
- Docker, Kubernetes, Terraform
- AWS, Google Cloud, Azure
- CI/CD Pipelines & Containerized Deployment
- PostgreSQL, MySQL, MongoDB, Neo4j
- Data Warehousing & Real-Time Streaming
- Vector Databases & Retrieval Pipelines
AI deal-sourcing pipeline that ingests YC startup data, enriches companies via web scraping, and scores them against a VC investment thesis using LLMs.
Key Highlights:
- Automated end-to-end VC analyst workflow: ingest → enrich → score → dashboard
- LLM scoring engine (Claude API) with structured JSON output validated by Pydantic
- Async Python backend (FastAPI + httpx) with rate-limited external calls
- React + TypeScript dashboard with filtering, sorting, and score breakdowns
- Dockerized multi-service architecture with CI/CD via GitHub Actions
🔗 https://github.com/HopeyCodeDS/venturesignal
End-to-end Retrieval-Augmented Generation system integrating vector search, LLM orchestration, and conversational memory.
Key Highlights:
- Reduced hallucinations using semantic retrieval pipelines
- Implemented LangChain agent workflows with tool calling
- Designed scalable FastAPI backend with vector database integration
🔗 https://github.com/HopeyCodeDS/RAG-based-chatbot-integration
AI system that automates extraction, validation, and structuring of logistics transport documents.
Impact:
- Reduced manual processing workload significantly
- Combined OCR, NLP, and validation pipelines
- Human-in-the-loop workflow for decision control
🔗 https://github.com/HopeyCodeDS/sortex-ai
Serverless API that answers natural-language queries against PDF documents using retrieval-augmented generation.
Impact:
- Grounded answers with source citations from uploaded PDFs
- Vector search (ChromaDB) + LLM (AWS Bedrock Claude) RAG pipeline
- Production-ready deployment on AWS Lambda via Docker
🔗 https://github.com/HopeyCodeDS/serverless-rag-api
OCR-powered application that automates warehouse label processing and matching workflows.
Features:
- Real-time label detection using computer vision
- End-to-end backend pipeline for document automation
- Mobile frontend integration for operational use
Backend: 🔗 https://github.com/HopeyCodeDS/automated-label-detection-and-matching-backend
Frontend: 🔗 https://github.com/HopeyCodeDS/automated-label-detection-and-matching-frontend
Containerized multi-service architecture deployed with Kubernetes for dynamic scalability.
Highlights:
- Microservices deployment using Docker & Kubernetes
- Auto-scaling and load balancing implementation
- Cloud-ready production architecture
🔗 https://github.com/HopeyCodeDS/multi-container-app
- NLP Sentiment Chat — Aspect-based sentiment analysis chatbot with local LLMs
- Mobility Application — Java transport management system
- CNN Emotion Recognition Model — Deep learning image classification system
- MineralFlow-KdG — Full-stack enterprise logistics platform with separate services: Frontend | Backend
👉 View all repositories: https://github.com/HopeyCodeDS?tab=repositories
LinkedIn:
https://www.linkedin.com/in/opeyemi-momodu-b92212b2/
Twitter / X:
https://twitter.com/opemomodu
I’m always open to collaborating on:
- AI system architecture projects
- LLM applications
- Multi-agent platforms
- Scalable cloud-based AI solutions
Feel free to connect or explore my work!