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Focusing on System Architecture
๐ŸŽฏ
Focusing on System Architecture

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Nehuen1304/README.md

Hi there! ๐Ÿ‘‹ I'm Nehuen Guevara

Software Engineer | Distributed Systems & Cloud Architecture

Computer Science Analyst (FaMAF, UNC) | GPA: 9.0/10

I focus on building robust software architectures, moving beyond traditional CRUD to solve critical engineering challenges: Massive Concurrency, Race Conditions, and Cloud Scalability. My approach combines deep systems knowledge ("under the hood" optimizations like Kernel/Network tuning) with modern AWS cloud infrastructure.


๐Ÿš€ Featured Engineering Projects

โ˜๏ธ Cloud-Native & Scalability

Systems designed for high availability, fault tolerance, and horizontal scaling.

AWS Redis Docker

  • Infrastructure: Architected on AWS using EC2 Auto Scaling Groups and Application Load Balancers (ALB) to handle traffic spikes.
  • Concurrency: Guaranteed transactional integrity and idempotency using Redis Lua Scripts for distributed locking.
  • Networking: Designed custom VPC isolation for secure data handling.

FastAPI WebSockets

  • Full-stack game engine achieving sub-100ms latency for concurrent players.
  • Implemented a hybrid SOA architecture using HTTP REST for transactions and WebSockets for real-time state streaming.

โš™๏ธ Systems & Core Engineering

Deep-tech implementations involving Kernels, Networks, and Distributed Computing.

Tech: C++17 OMNeT++ Networking

  • Engineered a robust transport layer over UDP implementing Flow Control and Cubic-style Congestion Control.
  • Achieved 0% packet loss and optimized channel utilization in high-stress network simulations.

Tech: C Operating Systems Kernel Hacking

  • Modified the xv6 OS kernel to implement a Multi-Level Feedback Queue scheduler.
  • Reduced average process turnaround time by 35% for CPU-bound workloads via dynamic priority aging.

Tech: Apache Spark Java Distributed Systems

  • Data pipeline optimizing network I/O and RDD partitioning for large-scale XML/JSON datasets.
  • Implemented fault-tolerance mechanisms based on distributed consensus principles.

๐Ÿ› ๏ธ Tech Stack & Tools

  • Languages: Python, C, C++, Java, Haskell, SQL.
  • Cloud & Infra: AWS (EC2, VPC, ALB, Auto Scaling, S3), Docker, CI/CD.
  • Backend: FastAPI, Redis (Lua/PubSub), Apache Spark, MongoDB.
  • Systems: Linux Kernel, TCP/IP Networking, Multithreading (Pthreads).
  • Methodologies: Agile (Scrum), Gitflow, TDD.

๐ŸŽฏ Looking For

I am currently looking for my first professional role as a Backend Engineer or Cloud Infrastructure Engineer, where I can apply my skills in optimization and architecture to solve real-world problems.

LinkedIn

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  1. realtime-multiplayer-game-platform realtime-multiplayer-game-platform Public

    Scalable multiplayer game engine built with FastAPI and React. Features real-time state synchronization via WebSockets, RESTful architecture, and strict Agile/Scrum development workflow.

    Python

  2. flash-sale-concurrency-engine flash-sale-concurrency-engine Public

    High-concurrency inventory engine demonstrating race condition mitigation using Redis Lua Scripts and FastAPI. Includes performance attack simulation with aiohttp.

    Python

  3. distributed-bigdata-processor-spark distributed-bigdata-processor-spark Public

    High-performance distributed system utilizing Apache Spark for massive RSS feed processing. Implements a MapReduce architecture for Named Entity Recognition (NER) with horizontal scalability and faโ€ฆ

    Java

  4. reliable-transport-protocol-cpp reliable-transport-protocol-cpp Public

    Reliable Transport Layer protocol implementation in C++ using OMNeT++ simulation (Congestion Control & Flow Control)

    C++

  5. xv6-kernel-scheduler-mlfq xv6-kernel-scheduler-mlfq Public

    Unix-like OS kernel modification implementing a Multi-Level Feedback Queue (MLFQ) scheduler and user-level semaphores. Optimized for process prioritization and starvation prevention.

    C

  6. functional-geometric-dsl functional-geometric-dsl Public

    Pure functional Domain Specific Language (DSL) for geometric modeling and compositional graphics. Implemented in Haskell using algebraic data types, higher-order functions, and recursive combinators.

    Haskell