Curriculum Vitae

03

SYSTEM SPECS (CV)

Professional Summary

Software Engineer with 5+ years of experience designing scalable microservices, cloud infrastructure, and high-performance backend systems. Specialized in building highly reliable architectures and optimizing application latency. Proficient in C++ and Python, with a strong focus on systems-level logic and modern web integration.

TECHNICAL SKILLS

C++ (Intermediate)80%
Python (Advanced)95%
Go75%
TypeScript70%
C#65%
Microservices Architecture90%
Docker / Kubernetes (GKE)85%
Google Cloud Platform (GCP)85%
CI/CD (Jenkins/GitHub Actions)80%
Redis / PostgreSQL75%
React (Basic)60%
Unreal Engine 570%

EDUCATION

Computer Science Certificate

Douglas College | 2025

B.S., Actuarial Science

Universidad Anáhuac | 2022

PROFESSIONAL EXPERIENCE

Feb 2023 - Present

LEAD SOFTWARE ENGINEER

Aper | Remote - Vancouver, BC
  • Microservices Architecture: Decomposed a monolithic application into 7 independent containerized microservices (Python/Go). Achieved a 34% improvement in p95 latency and tripled system throughput with zero downtime.
  • Performance Engineering: Architected an e-commerce benchmarking platform on GKE; optimized code to sustain 3x seasonal traffic spikes while reducing p95 latency to 205ms.
  • Reliability & CI/CD: Modernized the release pipeline using Jenkins and Docker, implementing parallel test sharding to reduce production build times by 54% (24m → 11m) and double deployment frequency.
  • System Integration: Built robust Python integration connectors for 3rd-party platforms, capturing 15+ real-time events per session to power user analytics and frontend dashboards.
  • Cost Optimization: Managed Kubernetes cluster efficiency, reducing infrastructure costs per 1,000 requests by 18% through resource optimization and auto-scaling policies.
Jan 2021 - Jan 2023

SOFTWARE ENGINEER (DATA INFRASTRUCTURE)

Aper | Remote - Mexico City
  • Pipeline Engineering: Migrated legacy batch processes to orchestrator-based workflows (Airflow), reducing job failure rates by 82% and cutting runtime from 4h 45m to <1h.
  • Backend Optimization: Designed and implemented streaming ingestion services that reduced data availability latency from T+24h to T+30m, enabling near real-time fraud detection.
  • Code Quality: Refactored legacy SQL/Python logic into modular, testable components, improving system maintainability and reducing technical debt.
2019 - 2020

JR. SOFTWARE DEVELOPER / ANALYST

Nielsen | Mexico City

Automation: Developed Python scripts utilizing Scikit-learn to automate manual statistical modeling, reducing preparation time from 3 days to 2 hours.

SOFTWARE PROJECTS

2023

REAL-TIME SIMULATION ENGINE

C++ & Unreal Engine 5 | Personal Project
  • Systems Logic: Engineered a performant C++ subsystem for real-time object state management, utilizing event-driven architecture to handle entity lifecycles and memory optimization.
  • UI Integration: Implemented C++ bindings for dynamic UI updates, managing real-time data flow between the core logic and the visual layer.
  • Relevance: Demonstrates strong C++ proficiency and complex state management logic required for hardware/software integrated devices.
2022

FRAUD DETECTION TRANSACTION ENGINE

Python & GCP | Personal Project
  • High-Volume Processing: Built a transaction processing engine capable of handling >50M transactions/day with low latency.
  • Production ML: Integrated gradient boosting models into a production API, effectively reducing fraud losses by 23%.