Senior Full-Stack Engineer and AI Systems Developer with 7+ years building scalable platforms across:
- AI / LLM systems
- SaaS platforms
- fintech systems
- enterprise architecture
- cloud infrastructure
I focus on engineering systems that evolve through:
Concept → Architecture → Production → Global Scale
Shows:
- coding hours
- language distribution
- weekly productivity
LLM assistant with:
- vector embeddings
- RAG retrieval pipeline
- AI memory layer
- LangChain orchestration
Features:
- forecasting models
- predictive analytics
- ML pipelines
- business intelligence outputs
https://market-mind-frontend.vercel.app
Architecture:
- LLM conversation engine
- embeddings search
- support workflow automation
Current areas of exploration:
- fine-tuning LLMs
- RAG retrieval optimization
- vector search scaling
- survival prediction models
- sales forecasting models
- AI vs human image detection
- inference optimization
- AI SaaS architectures
- distributed AI pipelines
Example AI platform architecture
flowchart TD
User --> API
API --> VectorDB
API --> Auth
VectorDB --> Retriever
Retriever --> LLM
LLM --> Response
Response --> User
Example scalable SaaS backend
flowchart TD
Client --> CDN
CDN --> LoadBalancer
LoadBalancer --> APICluster
APICluster --> Database
APICluster --> Cache
APICluster --> Queue
Queue --> Workers
Top repositories will automatically appear in your pinned section.
Recommended pinned repos:
- AI platform
- LLM tools
- distributed backend
- ML experiments
- infrastructure automation
Contributions focus on:
- backend infrastructure
- developer tooling
- AI engineering patterns
- distributed system designs
- English
- Igbo
- Hausa
linkedin.com/in/ukweheverest
Portfolio
relativity-codes.vercel.app
Great systems scale quietly.
The best architecture
solves today's problems
while anticipating tomorrow's complexity.