From Assembly Language to AI agents
My first “Hello, World” compiled in 2016, and I immediately wanted to know what happened underneath it. That question took me down through C to Assembly, and I loved it down there — registers, stack frames, the machine actually doing the work. Then back up to the web, where Python and JavaScript became the languages I’ve built in ever since.
I studied Quantitative Finance at the University of Ghana and went into fintech to digitise financial platforms — the start of six years across fintech, enterprise systems and backend infrastructure.
I still build across the stack; what’s changed is where it points. Since 2025 I’ve been moving into AI — training and evaluating LLMs at Turing, now building the services behind agentic platforms at Emergence AI.
Five teams, one throughline.
Owned backend APIs, authentication and platform services; resolved critical production issues and added observability across AI infrastructure.
Engineered scalable prompt-response pipelines in Python for large-scale LLM evaluations across 500K+ prompts. Built benchmarking systems to measure AI accuracy, latency, and reliability, and designed JSON-schema-based evaluation workflows for consistency validation.
Architected and maintained scalable databases and frontend systems for core services. Introduced Zustand state management and CI enforcement, while delivering AI-powered recruitment capabilities to improve candidate-job matching.
Improved UX and performance across client products, built Shopify admin tooling, and reduced infrastructure costs through AWS optimization and serverless adoption.
Built fraud detection and payment reconciliation systems, implemented USSD banking solutions, and supported fintech operations across African markets.
Tools I reach for.
Python
TypeScript
JavaScript
C++
React
Next.jsReact Native
ReduxZustand
FastAPI
Flask
Django
Node.js
Express
PydanticAIJSON Schema
NumPy
PandasPrompt EngineeringBeautifulSoup
Docker
Redis
Celery
Nginx
GitHub Actions
PostgreSQL
MySQL
MongoDB