Chris Knight is a Lead Software Engineer and Computational Physics PhD with 11 years of experience designing cloud-native, data-intensive systems and ML-enabled products. He blends low-level C/C++ HPC expertise with production Python and Go development, having built autoscaling Kubernetes pipelines, Spark-based analytics, and RAG-powered LLM applications for VC due diligence. Chris has led small engineering teams through product discovery to deployment—designing AWS and GCP infrastructure with Terraform, building APIs with FastAPI, and automating CI/CD for reliable delivery. His academic work on fluid–particle simulations taught him to wrangle TB-scale datasets and optimise parallel code, a practical discipline he’s applied to industrial digital twinning and automated design tools. Based in the UK, he pairs rigorous research-driven problem solving with product-minded engineering, and, less obviously, frequently prototypes solutions that marry C++ performance with Python operability.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computational Physics, Doctor of Philosophy (Ph.D.) Computational Physics at Imperial College London
MPhys + BSc Physics, MPhys + BSc Physics at University of Leeds
Example Docker setup for a Django app behind an Nginx proxy with Celery workers
Contributions:24 commits, 7 PRs, 25 pushes in 2 years 7 months
nginxdokkupythondocker-setupproxy
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Chris Knight - Lead Software Engineer at Brainpool AI / Tunedd