Perivitta Rajendran — an AI engineer passionate about building reliable AI systems. I enjoy bridging the gap between research and software engineering to create solutions that are practical, scalable, and built for real-world use.
My work revolves around machine learning, automation, and model experimentation. I enjoy designing systems that perform well but also make sense in the real world. I focus more on practical impact than chasing perfect metrics.
Through this site, I share technical articles, implementation guides, and lessons learned from building modern AI systems.
If you would like to talk about AI, data, or technology, feel free to reach out. I'm always happy to exchange ideas or collaborate on interesting projects.
Programs must be written for people to read, and only incidentally for machines to execute.— Harold Abelson
Focus areas
LLM Orchestration
Building AI workflows that combine language models, tools, and external systems into reliable applications.
RAG Pipeline Design
Designing retrieval pipelines that deliver relevant context through effective indexing, search, and evaluation.
Agentic Systems
Building and experimenting with AI agents that can reason, plan, and interact with external tools.
AI Evaluation
Measuring model quality with practical evaluation methods that support reliable, production-ready AI.
The badge wall
three cloud providers
Amazon Web Services
Google Cloud
Microsoft Azure
Let's build something together
Got a problem worth solving, a project in mind, or just want to talk shop about where AI is heading? My inbox is open.
Get in touch →