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kaziibwe alfred

@kaziibwealfred

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Backend & AI systems engineer building production LLM, RAG, and multi-agent platforms.

Uganda

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What I'm looking for

I’m looking to build production-grade backend and AI systems—especially LLMs, RAG, and agentic workflows—where I can own architecture-to-deployment, improve reliability and performance, and ship measurable business impact.

I’m a Software Engineer with 5+ years building production-grade systems—from scalable REST APIs and distributed backends to LLM-powered applications, RAG pipelines, and multi-agent orchestration platforms. I comfortably own the backend lifecycle (architecture, data pipelines, API design, CI/CD) and integrate AI capabilities directly into production systems.

At Tubayo, I designed and deployed LLM-powered solutions for real-time customer interactions and sales automation, including RAG pipelines grounded in Qdrant. I also led the Tai Agent Suite (multi-agent SaaS) using LangChain, CrewAI, and N8N, built event-driven pipelines with Kafka, and delivered secure REST APIs with DevSecOps practices. Previously, I migrated legacy monoliths to microservices and achieved 99.9% uptime while building an AI sign-language translation feature that improved accessibility by 40%.

Experience

Work history, roles, and key accomplishments

Freelance Back-End & AI

Independent

Jan 2024 - Jan 2025 (1 year)

Developed and integrated AI agents using LangChain and OpenAI APIs to analyze large datasets and deliver real-time business intelligence insights. Designed Deca-Easy, a modular Node.js/Laravel API toolkit (10 components) that increased development speed by up to 80%, and built a real-time event-driven auction platform using Node.js WebSockets.

Lang Chain OpenAI API Pandas Modular API Toolkit Design WebSockets API Development PHP Laravel

Education

Degrees, certifications, and relevant coursework

Self-Taught Software & AI Engineering

Self-Taught, Software Engineering & AI Engineering

Self-taught software and AI engineer with 5+ years of hands-on experience building production-grade web platforms, SaaS products, and AI/ML systems. Continuously upskilling via official documentation, open-source contributions, and AI engineering learning resources.