Summary
Edward Hartnett is a senior software engineer and AI practitioner with 16 years of experience building high-performance data and agentic systems, currently applying LLMs and RAGs to production AI apps in Boulder, Colorado. He has deep expertise in HPC I/O, parallel programming (MPI/OpenMP), and scientific data formats—most notably as an author and long-time maintainer of netCDF-4 and ParallelIO used broadly by NOAA, NASA, and climate modeling communities. Edward blends low-level C/C++/Fortran engineering with modern Python ML workflows, achieving engineering rigor (100% test coverage, zero warnings) while leading cross-disciplinary teams and large-scale deployments of forecasting systems. He pairs a background in electrical engineering with experience in embedded and telecom systems, plus program and proposal management, making him equally comfortable designing libraries, running operations, or shipping AI-driven analytics. A practical innovator, he often surfaces efficiency gains unseen by others—e.g., accelerating scientific I/O at scale that directly improves forecast throughput.
15 years of coding experience
34 years of employment as a software developer
Bachelor of Science (BS) Electrical and Electronics Engineering, Bachelor of Science (BS) Electrical and Electronics Engineering at Drexel University
Master of Science (MSc) Computer Software Engineering, Master of Science (MSc) Computer Software Engineering at Regis University
English