💻 Backend Engineer | Distributed Systems | AI Systems
🎓 M.S. Computer Science — University of Florida
🚀 Building scalable infrastructure, developer tools, and intelligent systems
I'm a backend-focused software engineer specializing in distributed systems, scalable APIs, and AI-powered platforms.
My work spans cloud infrastructure, data pipelines, compiler design, and agentic AI systems, with a strong focus on building production-grade systems that scale.
Currently working on large-scale climate data pipelines and HPC-based research infrastructure at the University of Florida.
• Distributed Systems
• AI Agent Infrastructure
• Data Pipelines & Research Platforms
• Backend Architecture
• Compiler Design
Java • Go • Python • C • SQL • JavaScript
Spring Boot • REST APIs • Microservices • Kafka • Redis
LLM APIs • Vector Databases • Data Pipelines • Zarr
PostgreSQL • MySQL • MongoDB • Redis
AWS • Docker • CI/CD • GitHub Actions
Python Scientific Stack • Climate Data Processing • HPC Workloads
A distributed agentic AI execution system that converts user requests into coordinated tasks executed by distributed workers.
flowchart LR
A[User Query] --> B[API Gateway / FastAPI]
B --> C[AI Planner Agent]
C --> D[Task Queue]
D --> E1[Worker Node 1]
D --> E2[Worker Node 2]
D --> E3[Worker Node N]
E1 --> F[Processing Engine]
E2 --> F
E3 --> F
F --> G[Vector Database]
G --> H[LLM Summarization Engine]
H --> I[API Response Returned]
• AI planner that decomposes complex tasks
• Distributed worker execution system
• Vector database knowledge storage
• LLM summarization pipeline
• Scalable queue-based architecture
Python • FastAPI • Redis • Celery • Vector DB • LLM APIs
High-performance distributed web crawler designed for large-scale data collection and indexing.
flowchart LR
A[Seed URLs / Scheduler] --> B[Crawl Queue]
B --> C1[Worker Node 1]
B --> C2[Worker Node 2]
B --> C3[Worker Node N]
C1 --> D[Fetcher Engine]
C2 --> D
C3 --> D
D --> E[HTML Parser]
E --> F[URL Extractor]
F --> B
E --> G[Content Processing]
G --> H[Storage Layer]
H --> I[Search / Index DB]
H --> J[Metadata DB]
• Distributed crawling workers
• Queue-based URL scheduling
• Rate limiting and politeness policies
• Content parsing and indexing
• Scalable horizontal architecture
Go • Kafka • Redis • PostgreSQL • Docker
Large-scale climate data pipeline and research platform developed at the University of Florida.
The platform integrates:
• NASA POWER weather datasets
• CHIRPS precipitation datasets
• Geographic shapefile-based site analysis
flowchart LR
A[NASA POWER API] --> D[Data Ingestion Pipeline]
B[CHIRPS Dataset] --> D
C[User Provided Shapefile] --> F[Geospatial Processor]
D --> E[Climate Data Processing]
E --> G[Zarr Data Store]
G --> H[Dataset Index Manager]
H --> I[Auto Dataset Updates]
F --> J[Site Dataset Generator]
G --> J
J --> K[ICASA File Generator]
J --> L[Visualization Engine]
L --> M[Interactive UI Dashboard]
K --> N[Downloadable Site Packages]
M --> O[Research Insights]
J --> P[HPC Execution Engine]
P --> Q[HiPerGator Cluster]
• Automated ingestion of climate datasets
• Zarr-based data storage and indexing
• Automatic dataset updates when new data becomes available
• HPC deployment on UF HiPerGator cluster
• Scientific experiment execution workflows
• Site-specific dataset generation via shapefiles
• Automated ICASA file generation
• Interactive UI for data visualization and insights
• Plot generation and data downloads
This platform replaces a previously manual research workflow, significantly reducing time required for climate data preparation for agricultural and environmental scientists.
Python • Zarr • Climate Data APIs • HPC (HiPerGator) • React • Data Visualization
Designed and implemented an object-oriented extension to Pascal with a full compiler pipeline.
• Classes and inheritance
• Access modifiers
• Semantic analysis
• LLVM IR code generation
ANTLR4 • LLVM • Compiler Design • Language Engineering
💼 LinkedIn https://linkedin.com/in/itswael
🌐 Portfolio https://itswael.github.io
📧 Email errwael@gmail.com
I enjoy building systems that replace manual workflows with automation — from AI task orchestration engines to research data pipelines that process climate datasets on HPC clusters.
⭐ Explore my repositories and feel free to collaborate!