Eytan Brodsky

• Owned Rust backend codebase for Downstream's custom content management system, Bridge.
• Communicated directly with client stakeholders concerning support, security, compliance and features.
• Led design and implementation of key features based on client requests and feedback.
• Led team-wide efforts and communicated with external security firm to facilitate penetration testing.
• Led team-wide efforts and communicated with New Relic representatives to implement app monitoring.
• Streamlized CI/CD processes, app version control and documentation for front and back ends.
• Optimized MongoDB queries to achieve over 30% speedup in costly database operations.
• Managed and executed AWS deployments (Terraform), version upgrades and feature delivery to numerous clients.
• Mentored teammates in Rust, testing strategies and best practices.

• Acted as a consultant for several small startups in person and remotely.
• Offered technical advice on design implementations, AWS architecture, CI/CD pipeline design and best practices.
• Contributed back-end code in C++, Rust, Go and Java in various different projects.
• Implemented system-level optimizations in Rust and C++ to improve the efficiency of critical components.
• Contributed to monitoring and benchmarking tools in Python.
• Mentored local engineers, offering advice and guidance for their work.
• Offered lessons in technical English to teams.

• Initiated and led development of a cloud management and optimization project written in Rust.
• Developed a declarative SQL-enhanced infrastructure and optimization language inspired by Terraform with Rust and PostgreSQL.
• Created an AWS network performance benchmarking tool in Python and built a developer API using Flask to access AWS performance metrics.
• Collaborated with clients to determine features and design feasible roadmaps for feature delivery.
• Managed and architected team AWS environments, providing support to developers and reducing costs.
• Set up and managed on-premise server environment, providing development and testing servers for teams.

• Facilitated weekly office hours, offering help to students and answering questions.
• Managed 12 student teams, each having 3-6 members.
• Resolved conflicts between teams and clients and facilitated collaboration.
• Oversaw weekly meetings with groups and clients, evaluating progress and grading work.

• Built and showcased computer vision demos in Python and C++ for industrial IoT applications.
• Built a neural network performance analysis tool, providing decision-driving datapoints and metrics.
• Worked on lower-level optimizations and tests in C++ for the neural network optimizer, identifying and removing performance bottlenecks.
• Developed PoCs and contributed to several papers on 802.11ax and time-sensitive networking at Intel Labs.

• Maintained several thousand servers in one of Intel's main data centers.
• Collaborated with server vendors to solve hardware issues and minimize downtime.
• Configured BIOS, network and hardware settings and performed standard maintenance on data center hardware.
• Streamlined data center operations with Python and Bash scripts for the team.

Crypto Exchange API

• A Rust project that interacts with the Coinbase and Kraken crypto exchanges.
• Provides a Rust API to interact with the exchanges' REST API and websocket endpoints.
• Provides a declarative language for monitoring specific coin pairs and defining triggers and actions based on real-time market data.
• Implemented micro-optimizations to improve hot-path efficiency and minimize latency.

DNS Resolver

• Implemented a recursive DNS resolver in Rust.
• Followed the specifications in RFC 1035 to interact with DNS servers.
• Added a packet information visualization tool similar to hexdump to more easily see information contained in each DNS packet.

Convex Optimization Heuristic for Priority and Time Constrained Packet Scheduling

• Implemented a MATLAB simulation of a single hop star network to simulate packet switching between virtual machines with a unique scheduling technique to improve efficiency with high and low priority workloads.

Autonomous Vehicle Routing in Congested Networks

• Created an interface for autonomous vehicle research that showed a transportation network operating based on different parameters.
• Implemented different algorithms to figure out optimal routing based on locations of other vehicles and traffic congestion prediction.
• Heavily used Numpy, Pandas and Matplotlib for result and data visualization and mathematical optimization.