Richard Cownie is a Principal Software Engineer with deep expertise in high-performance systems, distributed databases, and hardware-aware optimization, bringing over two decades of experience across startups and established engineering teams. He has led and shipped scalable database and data-processing innovations—from off-heap C++ kernels for petabyte-scale genomics to cloud-native columnar storage and photonic ML accelerator simulations—while improving ingest and migration tooling at companies like Oracle, Broad Institute, Paradigm4, MongoDB, and Positron AI. Richard is particularly skilled at finding the 10% of effort that delivers 90% of the performance win, with specialties in compression, algorithm and data-structure design, and matching software to bandwidth/latency constraints. He combines low-level skills (stackless x86 assembler, simulator work) with modern C++-17 parallel/distributed engineering, and has a track record of moving JVM/Scala pipelines into compact, high-throughput native implementations. Based in Brookline, MA, he balances technical leadership with hands-on coding and a pragmatic focus on team productivity and measurable system bottleneck reduction. An oft-overlooked strength is his ability to design repeatable parallelism models that provide deterministic behavior in high-concurrency systems, a through-line from EDA tools to modern database kernels.
8 years of coding experience
29 years of employment as a software developer
M.Sc., Computer Systems Engineering, M.Sc., Computer Systems Engineering at Edinburgh University
B.A., Mathematics, B.A., Mathematics at Cambridge University
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Richard Cownie - Principal Software Engineer at Positron AI