Razieh Behjati is a Principal Software Engineer in ML with a decade of experience building secure, production-ready back-end and ML systems across startups and large tech companies, currently at UiPath after a multi-year tenure at Google. Her background spans machine learning engineering, DevOps, security-focused build systems and distributed systems research—anchored by a PhD in Software Engineering from the University of Oslo and an MSc in AI. She has hands-on open-source impact on security and CI/CD tooling, contributing to notable projects like Google’s OSS-Fuzz and the SLSA GitHub provenance generator to improve supply-chain and fuzz-testing reliability. Comfortable moving between research-grade architectures and pragmatic production deployments, she’s known for refactoring complex gRPC systems, introducing protobuf-based logging, and implementing practical build/validation commands in tooling. Her career blends deep academic rigor with entrepreneurial and leadership experience (including a CTO role), which helps her bridge long-term system design with measurable operational improvements.
10 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD) Computer Software Engineering, Doctor of Philosophy (PhD) Computer Software Engineering at University of Oslo
M.Sc Artificial Intelligence, M.Sc Artificial Intelligence at University of Tehran
Meaningful control of data in distributed systems.
Role in this project:
Back-end Developer
Contributions:1042 reviews, 218 commits, 500 PRs in 2 years 9 months
Contributions summary:Razieh's commits focused on refactoring the codebase, particularly concerning the naming and structure of gRPC-related components. The user refactored the logging functionality into a dedicated module and transitioned from a string-based to a protobuf-based LogEntry structure, enhancing the system's robustness. Furthermore, the user made changes in the GRPC compiler and added more features for measuring grpc streaming messages sent by the server. These changes demonstrate an understanding of back-end systems and optimization for a distributed system.
Language-agnostic SLSA provenance generation for Github Actions
Role in this project:
Back-end & DevOps Engineer
Contributions:50 reviews, 7 commits, 12 PRs in 1 month
Contributions summary:Razieh primarily contributed to the development of a command-line tool for generating SLSA provenance for artifacts built using a Docker builder image, focusing on functionality related to generating and storing build definitions. Their work involved adding a `dry-run` command and a `build` command, which handle user input, validate it, and create a build definition. Code changes involved modifying existing files and adding new files to handle configuration, parsing, and build functionality within the specified Docker-based build system.
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Razieh Behjati - Principal Software Engineer In ML at UiPath