I'm a backend-focused software engineer passionate about building scalable systems that automate and optimize real-world processes.
Currently, I'm working on:
- 🔄 Offer processing pipelines for platforms like Takealot — scalable Django + Celery systems that handle price tracking, updates, and API-based automation
- 🧠 AI agents for call centers — using OpenAI, LangChain, and FastAPI to assist human agents with transcription, summarization, sentiment analysis, and more
- Languages: Python · JavaScript (basic)
- Frameworks: Django · FastAPI · Celery
- Tools: Redis · PostgreSQL · Docker · Git
- Cloud & Infra: Azure · AWS · Railway · WSL · GitHub Actions
- AI/ML: OpenAI APIs · LangChain · PGVector
- Exploring: Kubernetes · Streaming pipelines · LLM-based agents
Building the backend for an AI-powered assistant that integrates WhatsApp, WooCommerce, and Retrieval-Augmented Generation (RAG).
🔧 Tech Stack: FastAPI · LangChain · OpenAI · PGVector · PostgreSQL
💡 Use Case: Helps automate customer service and call center tasks like transcription, summarization, and sentiment analysis
📦 Highlights:
- Modular FastAPI endpoints
- Embedding storage and retrieval using PGVector
- Integrated with real-world platforms (WhatsApp, WooCommerce)
- RAG pipeline powered by LangChain + OpenAI
Building a distributed offer processing system for Takealot sellers using public and private APIs.
- Uses Django, Celery, and Redis to manage fetching, processing, and updating offers
- Entity-based concurrency with horizontal scaling
- Built for high-throughput, near real-time updates
My goal is to automate backend processes with AI and build a robust, scaled infrastructure.
- ✉️ [email protected]
- 🧩 Ask me about: backend architectures, distributed systems, API scaling, or LLM integration
“Build systems that scale, automate what matters, and always be learning.”