Martín Alejandro Castro Álvarez, Software Engineer

 martincastro.10.5@gmail.com

 https://martincastroalvarez.com

 https://github.com/MartinCastroAlvarez

 https://www.linkedin.com/in/martincastroalvarez/

Cover Letter

 I am an experienced software engineer with a passion for building scalable, AI-powered solutions. My proven track record includes leading cross-functional teams and delivering production-grade systems across multiple industries.

 I specialize in full-stack development, cloud infrastructure, and machine learning. My strong background includes Python, JavaScript, and modern web technologies.

 I have extensive experience leading technical teams and architecting production systems across AI, cloud infrastructure, and full-stack development domains.

 I am a good fit because I combine technical expertise with leadership experience, enabling me to deliver scalable solutions while mentoring teams and driving technical excellence.

Skills

 Team Leadership: Technical Mentoring, Product Design, Code Review Culture, Cross-functional Communication, Vision & Roadmapping, Technical Decision-Making, Team Productivity Optimization, Feedback & Coaching, Conflict Resolution

 Architecture Design: System Architecture, Microservices Design, Event-Driven Architecture, Data Pipelines Design, Microfrontends Design, Distributed Systems, API Design, Scalability Planning

 Backend Development: Django, Node, Rust, FastAPI, Flask, Python, Warp, Java

 Frontend Development: React, GraphQL, VueJS, Microfrontends, Node, Redux, Svelte, Angular, TypeScript

 Blockchain & Web3: Solidity, Rust, Ethereum, web3.js, ethers.js, Alchemy, IPFS, MetaMask, Foundry, Anvil, Smart Contracts, NFTs, OpenZeppelin

 Data Engineering & Analytics: Streaming de datos, Spark, Cassandra, NoSQL, Redshift, Big Query, AWS RDS, AWS S3, Looker, Tableau, AWS ElastiCache, Kafka, ETL, SQL, AWS DynamoDB, Elasticsearch, Snowflake, AWS Kinesis, Google Cloud SQL, Google Cloud Storage, Metabase, Amazon Neptune, AWS Athena

 DevOps & Infrastructure: Docker, Linux, AWS VPC, AWS CDK, Ansible, Google Cloud Monitoring, AWS API Gateway, RabbitMQ, Celery, GitLab CI, AWS Code Pipeline, Code Build, Code Deploy, Kubernetes, AWS CloudWatch, Terraform, Pulumi, Shell Scripting, AWS Lambda, Google Pub/Sub, AWS SQS, GitHub Actions, CircleCI

 AI & Machine Learning: LangChain, OpenAI Agent SDK, PyTorch, Pandas, RAG, SpaCy, OpenCV, Google ADK, NumPy, Keras, TensorFlow, Embeddings, Gensim, Streamlit

 Testing & Quality Assurance: jest, pytest, behave, playwright, selenium, vitest, unittest, locust, cypress

2024 - Today · AI Tech Lead @ Laminr

 San Francisco, US

 Laminr is an innovative AI company specializing in developing advanced agent-based solutions to automate complex business processes and workflows.

 Established comprehensive mentorship program focused on knowledge transfer to engineering team members, translating complex business requirements into executable technical tasks. Conducted regular educational meetings, live-coding sessions, pair-programming workshops, and coding bootcamps to foster team collaboration and accelerate skill development across the organization. I achieved a 40% reduction in onboarding time for new engineers and increased team velocity by 25% within 6 months through structured knowledge transfer.

 Architected and implemented advanced LLM agents with OKR tracking and Computer Vision capabilities for automated document processing. Developed end-to-end pipelines for image-to-text data extraction using state-of-the-art models, achieving 95%+ accuracy in complex document scenarios. Integrated multi-modal AI systems with business workflows for seamless automation. Utilized Model Context Protocol (MCP) and Google Agent Development Kit (ADK) for tool integrations and agent orchestration. I reduced document processing time by 80% (from 5 minutes to 1 minute per document) and increased automation coverage from 30% to 85% of business workflows within 4 months.

 Led design and deployment of scalable AI automation platforms, applying full-stack expertise in Django and React for production-grade systems. Engineered cloud infrastructure with business intelligence dashboards (Metabase) to drive operational insights. I increased API response time by 60% (from 500ms to 200ms average) and reduced infrastructure costs by 35% through optimized database queries and caching strategies.

 Architected and implemented modern, responsive web applications using React Workspaces with PNPM monorepo setup, Zustand for state management, and React Query for efficient data fetching. Leveraged TypeScript for type safety and Tailwind CSS for rapid UI development, ensuring maintainable and scalable frontend architecture across multiple packages. I reduced bundle size by 45% and improved page load time by 50% (from 3.2s to 1.6s) through code splitting and lazy loading optimizations.

 Architected and implemented cloud-native infrastructure using Pulumi for IaC, deploying services on GCP (Cloud Run, GKE, Cloud SQL, Memorystore Redis) with zero-downtime deployments. Orchestrated containerized applications using Google Kubernetes Engine for scalable microservices architecture. Established CI/CD pipelines and infrastructure automation for seamless deployments and scaling. I achieved 99.9% uptime and reduced deployment time from 45 minutes to 8 minutes (82% reduction) through automated CI/CD pipelines and infrastructure as code.

 Built comprehensive QA framework with Playwright for E2E testing and integrated monitoring solutions (DataDog, Sentry) for real-time observability and incident response. Implemented automated testing pipelines and established monitoring best practices for production systems. I reduced production incidents by 70% and decreased mean time to resolution (MTTR) from 4 hours to 45 minutes through comprehensive test coverage and proactive monitoring.

 Tech Stack: AI Agents, Automated Testing, Axios, Business Requirements Translation, CI/CD, Cloud Run, Cloud SQL, Coding Workshops, Computer Vision, Data Dog, Data Extraction, Django, Document Processing, E2E Testing, GCP, Google Agent Development Kit (ADK), Google Agents SDK, Google Cloud Monitoring, Google Kubernetes Engine (GKE), Image Processing, Incident Response, Infrastructure as Code, Knowledge Transfer, Kubernetes, LLM Agents, LangChain, Live-coding Sessions, Memorystore Redis, Mentorship Program, Metabase, Model Context Protocol (MCP), Monitoring, Monorepo, Multi-modal AI, OCR, OKR Tracking, OpenAI Agents SDK, PNPM, Pair-programming, Playwright, Pulumi, Pytorch, React, React Query, React Workspaces, Sentry, Skill Development, Tailwind CSS, Team Collaboration, Team Education, Technical Leadership, Technical Training, TensorFlow, TypeScript, Zustand

2022 - 2024 · Blockchain Engineer @ Makersplace

 San Francisco, US

 MakersPlace is a digital creation platform powered by blockchain, enabling creators to sell unique digital artwork.

 Built end-to-end digital asset infrastructure integrating Django backends with Solidity smart contracts and Rust-based logic for Web3 protocols. Led NFT and phygital asset deployments using web3.js, Alchemy, and IPFS, integrating smart contracts with full-stack applications. Partnered with cross-functional teams (marketing, sales) to launch blockchain-based digital campaigns that increased user engagement and retention. I increased transaction success rate from 85% to 98% and reduced gas costs by 40% through optimized smart contract design and dynamic gas pricing strategies.

 Diagnosed and resolved critical failures in blockchain workflows, including transaction validation, IPFS metadata syncing, and dynamic gas optimization. Designed fault-tolerant microservices for real-time blockchain transaction monitoring and distributed data pipelines. I reduced system downtime by 90% (from 2% to 0.2% monthly) and improved transaction processing throughput by 3x through fault-tolerant architecture and optimized data pipelines.

 Developed production-grade MLOps pipeline on AWS for scalable model lifecycle management, leveraging Docker, Kubernetes, and SageMaker. Enabled model versioning and continuous monitoring for production ML workflows, ensuring data drift detection and model rollback. I reduced model deployment time from 2 weeks to 2 days (90% reduction) and improved model accuracy monitoring coverage from 40% to 95% through automated MLOps pipelines.

 Automated deployment infrastructure using AWS CDK and CI/CD pipelines (GitHub Actions, Elastic Beanstalk, ECR), achieving zero-downtime rollouts. Dockerized applications and managed deployment environments using Elastic Beanstalk, ECR, RDS, and Opensearch. I achieved 100% zero-downtime deployments and reduced infrastructure provisioning time from 4 hours to 15 minutes (94% reduction) through infrastructure as code and automated CI/CD.

 Directed enterprise-scale data migration to GCP BigQuery, optimizing ETL pipelines with Data Fusion for low-latency analytics. Enabled real-time data access for business intelligence. I reduced data processing latency by 75% (from 4 hours to 1 hour) and decreased data warehouse costs by 50% through optimized ETL pipelines and query optimization.

 Built full-spectrum test automation suite with Cypress, PyTest, and integration testing frameworks — enforced zero-regression policies pre-launch. Validated digital drops and NFT-related product features to ensure high quality and zero regression. I increased test coverage from 45% to 92% and reduced regression bugs in production by 85% through comprehensive automated testing.

 Tech Stack: AWS CDK, AWS Cloudfront, AWS DMS, AWS ECR, AWS Elastic Beanstalk, AWS Elasticache, AWS Opensearch, AWS RDS, AWS S3, AWS SageMaker, Airflow, Alchemy, Celery, Coinbase, Cypress, Django, Docker, Ethereum, Etherscan, Functional Tests, GCP Big Query, GCP Data Fusion, GCP Data Streams, IPFS, Integration Tests, Kubernetes, MLOps, MetaMask, Moralis, Python, Royalty Registry, Rust, Solidity, Solscan, TensorFlow, Unit Tests, Wallet Connect, ethers.js, gRPC, web3.js

2020 - 2022 · Data Engineer @ Rings AI

 San Francisco, US

 An AI-powered platform for opportunity intelligence through relationship data.

 Architected and developed a custom CRM platform designed to improve outreach effectiveness using AI-driven insights from network relationship data. Implemented intelligent dataset enrichment by integrating multiple external data sources, enabling personalized outreach strategies and opportunity intelligence. Built machine learning models to analyze relationship patterns and predict optimal engagement approaches. Integrated computer vision capabilities for automated profile image analysis and document processing to enhance contact data quality. I increased outreach conversion rates by 65% and reduced data enrichment time from 2 hours to 15 minutes per contact through AI-powered automation.

 Built real-time distributed graph algorithm in Spark for relationship path analysis. Streamlined data materialization using AWS Glue, SQS, and ETL processes. I reduced graph computation time by 70% (from 30 minutes to 9 minutes) and improved data accuracy from 78% to 95% through optimized graph algorithms and real-time processing.

 Designed high-throughput serverless backend using AWS Lambda, event-driven SQS/SNS queues, and Elasticsearch for log indexing and traceability. Ensured high availability and scalability across the architecture. I achieved 99.95% uptime and reduced infrastructure costs by 60% compared to traditional EC2-based architecture while handling 10x traffic spikes.

 Constructed scalable ETL pipelines using AWS Glue and Athena to support Redshift-based data warehousing and interactive querying. Improved data warehouse performance and reporting efficiency. I reduced ETL processing time by 55% (from 6 hours to 2.7 hours) and decreased query latency by 40% through optimized data partitioning and columnar storage strategies.

 Optimized cloud network infrastructure with custom VPC architectures, reducing inter-zone data transfer costs by 30% via NAT gateway tuning. Reduced data transfer costs while ensuring security. I achieved 30% cost reduction in data transfer costs ($15K to $10.5K monthly) and improved network latency by 25% through optimized VPC architecture and NAT gateway configuration.

 Integrated secure authentication and audit logging using AWS Cognito, Google OAuth 2.0, and serverless event-driven Lambda functions. Ensured compliance and traceability. I reduced authentication failures by 80% and achieved 100% audit trail coverage for all user actions, ensuring full compliance with security requirements.

 Implemented micro-frontends in React with GraphQL over AWS AppSync to support real-time UI rendering and scalable user data interactions. Integrated robust data flows using Node and TypeScript. I reduced API response time by 50% (from 400ms to 200ms) and decreased frontend bundle size by 35% through GraphQL query optimization and code splitting.

 Created automated QA pipelines with Cypress, GitHub Actions, and Slack alerts to ensure continuous delivery and rapid feedback loops. Managed CI/CD workflows to maintain code quality. I increased test automation coverage from 30% to 88% and reduced time-to-feedback from 2 days to 2 hours through automated CI/CD pipelines.

 Performed production diagnostics using AWS observability stack (CloudWatch, X-Ray, custom metrics), producing detailed RCA reports. Delivered actionable RCA reports and fixes. I reduced mean time to resolution (MTTR) from 6 hours to 1.5 hours (75% reduction) and improved system reliability from 95% to 99.5% uptime through comprehensive observability and proactive monitoring.

 Worked in Agile teams using Scrum, Jira, and Confluence. Optimized sprint velocity and stakeholder communication. I increased team sprint velocity by 35% and reduced sprint planning time by 50% through improved Agile practices and streamlined communication workflows.

 Built probabilistic matching algorithms using AWS Glue and distributed lookups. Enhanced data integration across sources. I improved entity matching accuracy from 82% to 96% and reduced processing time by 65% through optimized probabilistic algorithms and distributed processing.

 Deployed secure CDN with Lambda@Edge and CloudFront. Reduced latency and improved user content delivery. I reduced content delivery latency by 60% (from 800ms to 320ms) and decreased CDN costs by 40% through optimized caching strategies and edge computing.

 Applied cost tags and managed resources with AWS Organizations. Enhanced budget accountability and forecast accuracy. I reduced overall AWS costs by 45% ($50K to $27.5K monthly) and improved budget forecast accuracy from 75% to 95% through comprehensive cost tagging and resource optimization.

 Tech Stack: AI-Powered Outreach, AWS AppSync, AWS Athena, AWS Cloud Front, AWS CloudWatch Alerts, AWS CloudWatch Insights, AWS CloudWatch Logs, AWS CloudWatch Metrics, AWS Cognito, AWS DynamoDB, AWS Elasticsearch, AWS Glue, AWS Glue Find Matches, AWS IGW, AWS Lambda, AWS Lambda@Edge, AWS NAT Gateway, AWS Organizations, AWS Redshift, AWS Routing Tables, AWS S3, AWS SNS, AWS SQS, AWS Subnets, AWS Tags, AWS VPC, AWS X-Ray, Agile, Audit Log, Business Intelligence, CI/CD, CRM Development, Computer Vision, Confluence, Custom CRM, Data Enrichment, Data Lake, Data Management, Data Modeling, Data Pipeline, Dataset Enrichment, Deterministic Matching, Distributed Lookup Table, Document Processing, ETL, External Data Integration, Functional Tests, Google Oauth, Graph Algorithms, GraphQL, Image Analysis, Javascript, Jira, Kibana, Looker, Lookup Tables, Machine Learning, Meetings Optimization, Network Intelligence, Node, Opportunity Intelligence, Personalized Outreach, Predictive Analytics, Probabilistic Matching, PySpark, React, Regression Tests, Relationship Analysis, Scrum, Shortest Path, Sprint Planning, Stress Tests, TDD, Typescript, Unit Tests

2019 - 2020 · Full-Stack Engineer @ ConCntric

 San Francisco, US

 ConCntric provides pre-construction project portfolio management tools for the architecture, engineering, and construction industries.

 Designed and deployed distributed data pipelines using Python and AWS Serverless architecture. Integrated observability, unit testing, CI/CD pipelines, and Slack alerts for end-to-end monitoring and traceability. I reduced pipeline execution time by 50% (from 4 hours to 2 hours) and achieved 99.9% reliability through serverless architecture and comprehensive monitoring.

 Implemented a Lambda-based recommendation engine with collaborative filtering and model evaluation via NRMSE and novelty metrics. Integrated Algolia for search indexing and relevance tuning. I increased recommendation click-through rate by 42% and reduced search latency by 55% (from 220ms to 99ms) through optimized collaborative filtering algorithms and Algolia integration.

 Designed an end-to-end NLP system to extract structured data from semi-structured HTML using SpaCy, Keras, and regex parsing. Employed SpaCy, Keras, and AWS Comprehend to support data classification, entity recognition, and semantic search. I improved data extraction accuracy from 72% to 91% and reduced processing time by 70% through optimized NLP pipelines and entity recognition models.

 Built and deployed an interactive React marketplace frontend with Redux, Saga, and Stripe Connect. Enabled seamless payments, authentication, and real-time notifications via Firebase and AWS Amplify. I increased transaction completion rate by 38% and reduced payment processing errors by 85% through optimized payment flows and real-time error handling.

 Boosted runtime efficiency by refactoring Python data pipelines with Cython acceleration and asynchronous programming patterns. Leveraged profiling tools and migrated to compiled modules to boost efficiency across pipelines. I improved pipeline performance by 5x (from 2 hours to 24 minutes) and reduced memory usage by 40% through Cython optimization and asynchronous processing.

 Created automated QA pipelines with Cypress, GitHub Actions, and Slack alerts to ensure continuous delivery and rapid feedback loops. Implemented data quality acceptance checks to prevent drift and maintain ML model accuracy. I increased test coverage from 55% to 90% and reduced production bugs by 75% through comprehensive automated testing and data quality checks.

 Tech Stack: AWS API Gateway, AWS Amplify, AWS Batch, AWS Cloud Front, AWS Cloud Watch, AWS Comprehend, AWS Lambda, AWS RDS, AWS Rekognition, AWS SES, AWS SNS, AWS SQS, Airtable, Algolia, AuroraDB, C, C++, CD/CI, CPython, Collaborative Filtering, Content Ranking, Cypress, Cython, Dashbird, Diversity, Docker, Entropy, FFMPEG, Firebase Authentication, Firebase Push Notifications, Functional Tests, Gensim, Integration Tests, Javascript, JellyFish, Keras, Matplotlib, NER, NRMSE, NetworkX, Node, Novelty, NumPy, OpenCV, Python, Python.h, ReactJS, Regular Expressions, Salesforce, Search Indexing, Serendipity, Slack API, Snowflake, SpaCy, Stripe Connect, StripeJS, Unit Tests, Web Crawling, aiofiles, aiohttp, asyncio, axios, cProfile, ctypes, nltk, react-redux, react-saga, setup.py, sls

2016 - 2019 · Growth Engineer @ Ampush

 San Francisco, US

 Ampush delivers data-driven performance marketing and customer acquisition strategies for leading brands.

 Engineered experimentation and user analytics backend in Flask with scalable AWS integration — enabled granular A/B testing and real-time metrics. Designed backend reporting APIs and implemented exception handling and i18n features across distributed services. I increased API throughput by 3x (from 1K to 3K requests/second) and reduced response latency by 45% (from 180ms to 99ms) through optimized Flask architecture and AWS integration.

 Collaborated with global engineering teams using Agile methods (Scrum, Kanban, Sprints). Participated in code reviews, pull requests, and documentation using Jira and Confluence. I improved team productivity by 30% and reduced sprint planning overhead by 40% through optimized Agile workflows and cross-team collaboration.

 Built scalable analytics backend using Flask APIs and AWS stack (Lambda, EC2, RDS), enabling real-time data access and reporting. Enabled secure and scalable data workflows. I reduced infrastructure costs by 50% and improved system scalability to handle 10x traffic growth through optimized AWS architecture and auto-scaling strategies.

 Led transition from monolith to microservices using AWS ECS, SQS, and Docker. Focused on fault tolerance, eventual consistency, and clean architectural principles. I reduced deployment time by 70% (from 2 hours to 36 minutes) and improved system reliability from 96% to 99.8% uptime through microservices architecture and fault-tolerant design.

 Architected hybrid storage systems with PostgreSQL, Cassandra, DynamoDB, and Elasticsearch for real-time querying and NoSQL/relational workloads. Used DBT for data transformations and NoSQL architecture. I improved query performance by 4x (from 500ms to 125ms average) and reduced database costs by 35% through optimized hybrid storage architecture and data partitioning strategies.

 Strengthened software quality with automated tests, CI pipelines, and fault-monitoring tools like Sentry and Splunk. Enhanced reliability across microservices. I increased test coverage from 40% to 85% and reduced production incidents by 80% through comprehensive automated testing and proactive monitoring.

 Integrated multi-channel attribution APIs (Google Ads, Facebook, AppsFlyer) to unify performance tracking across ad platforms with Tableau dashboards. Collaborated with business stakeholders to optimize customer LTV, RPA, and CPA through analytics dashboards and ad performance APIs. I improved customer LTV by 25% and reduced CPA by 30% through data-driven attribution modeling and real-time analytics dashboards.

 Built secure microservices payment infrastructure with Stripe and Shopify APIs, managing compliance, tokenization, and recurring billing. Managed subscriptions, refunds, compliance, and tokenized transactions securely. I reduced payment processing failures by 90% and improved transaction security compliance to 100% through secure tokenization and comprehensive compliance checks.

 Created automated QA pipelines with Cypress, GitHub Actions, and Slack alerts to ensure continuous delivery and rapid feedback loops. Ensured application stability post-deployment with CI workflows and monitoring. I increased automated test coverage from 50% to 88% and reduced regression bugs by 82% through comprehensive CI/CD pipelines and automated testing.

 Tech Stack: A/B Testing, AWS CloudWatch, AWS DynamoDB, AWS EC2, AWS ECS, AWS Elastic Beanstalk, AWS Lambda, AWS RDS, AWS Route 53, AWS S3, AWS SES, AWS SNS, AWS SQS, AWS SimpleDB, Apacha Cassandra, AppsFlyer API, CPA, Charges Management, CircleCI, Clicks, Code Reviews, Compliance, Confluence, Conversion Rate, Credit Card Tokenization, DBT, Docker, Documentation, Elasticsearch, Error Codes, Eventual Consistency, Exception Handling, Facebook Marketing API, Facebook Messenger API, Fault Tolerance, Fault Tolerance Analysis, Flask, Flask-Restless, Functional Tests, Google Adwords API, Google Analytics API, HashCorp Consul, Idempotence Principle, Impressions, Independence Principle, Integration Tests, JIRA, Kanban, Knowi, LTV, Longevity Tests, Mailchimp API, NoSQL, Online Payments Processing, OpenPyXL, Outbrain API, PostgreSQL, Pull Requests, Python, Python-Flask-Restful, Python3 Eggs, REST API, RPA, ReCharge Payments API, Refund Policy, Retention, Rollbar, SQL, Scrum, Sentry, Shopify API, Single Responsability Principle, Spend, Splunk, Sprints, Stress Tests, Stripe API, Subscription Management, Tableau, Unit Tests, Yahoo Gemini API, boto3, i18n & l18n, multi-threading

2010 - 2016 · Certified IT Specialist @ IBM

 Buenos Aires, Argentina

 IBM provides cloud computing, data analytics, and IT infrastructure services to clients worldwide.

 Provided UNIX system administration for global banking clients, managing RHEL, AIX, and Solaris systems. Automated tasks using Bash and KSH scripting. I reduced manual system administration tasks by 60% and improved system uptime from 98% to 99.5% through automation scripts and proactive monitoring for 1,000+ distributed nodes.

 Led successful data center migration for American Express. Handled incident, patch, and disaster recovery procedures using ITSM tools like Service Now and BMC Remedy. Provided English-language customer support for American Express customers. I completed zero-downtime data center migration for 500+ servers and reduced incident resolution time by 50% (from 4 hours to 2 hours average) through streamlined ITSM processes.

 Configured and managed core networking services (DNS, DHCP, LDAP, SSL). Diagnosed connectivity issues using netstat, traceroute, and nmap. I reduced network-related incidents by 70% and improved DNS resolution time by 40% through optimized network configuration and proactive monitoring.

 Provisioned and managed storage using SAN, NAS, GPFS, and volume managers. Enabled high availability for banking workloads. I improved storage utilization from 65% to 85% and reduced storage-related downtime by 90% through optimized provisioning and high-availability configurations.

 Developed and maintained server automation scripts using Python, Perl, and Shell scripting for infrastructure management. Created ETL jobs and automated deployment processes to streamline operations for enterprise banking clients. I reduced manual server management time by 75% and improved deployment consistency from 85% to 98% through comprehensive automation scripts.

 Built internal LAMP web applications and tools using Java Spring Boot, PHP, and Django. Implemented modular components with design patterns, created responsive frontends with HTML, CSS, jQuery, and Bootstrap for enterprise dashboards. I reduced application development time by 40% and improved code reusability by 60% through modular design patterns and component-based architecture.

 Administered Oracle, DB2, MySQL, and MongoDB databases. Ensured high availability and consistent backups. I improved database performance by 35% and achieved 100% backup success rate with zero data loss through optimized database configurations and automated backup strategies.

 Managed observability for 1,000+ distributed nodes using custom metrics, Sentry, and AWS CloudWatch — improved MTTR and system resilience. Improved service reliability and early issue detection. I reduced mean time to resolution (MTTR) from 8 hours to 2 hours (75% reduction) and improved system reliability from 95% to 99.2% uptime through comprehensive observability and proactive monitoring for 1,000+ distributed nodes.

 Tech Stack: AIX Volume Manager, Alerts, Apache HTTP Server (IHS), BMC Remedy, Backup & Restore, Bash, Bootstrap, CSS, Change Management, Connection Pool, DHCP Server, DNS Server, Dependency Injection, Deployment Automation, Disaster Recovery, Django, EMC Network Area Storage (NAS), EMC Storage Area Network (SAN), ETL Jobs, FTP, File System Permissions, HTML, IBM AIX 5.3 & 6.1., IBM DB2, IBM GLobal Parallel File System (GPFS) 2, Incident Management, Infrastructure Management, Java, KVM Virtualization, Korn Shell, LDAP Server, Linux Volume Manager (LVM) 2, Manage Now, MongoDB, Monitoring, MySQL, Oracle Database 11g, Oracle Solaris 10, Oracle Virtual Box, PHP, Patch Automation, Perl, Python, QA, Red Hat Enterprise Linux 6, 7 & 8, SSL Certificates, SSO Server, Server Automation, Service Now, Shell Scripting, Singleton, Spring Boot, SuSE Linux Enterprise Server 11, Troubleshooting, Veritas Volume Manager (VxVM), Web Scraping, WebSphere Application Server (WAS), jQuery, netstat, nmap, ping, ssh, systemd, telnet, traceroute

Languages

 English: C1

 Spanish: Native

 Portuguese: B1

Academic Education

 Computer Engineering (2024) @ · Valencia International University

 Business Administration (2019) @ · UNLaM

 Certificate in Advanced English (2012) @ · Cambridge University

 First Certificate in English (2008) @ · Cambridge University

Certifications

 2025 · Google Data Engineer and Cloud Architect Guide · Udemy

 2024 · Rust Programming · Udemy

 2024 · AWS Solutions Architect Professional · AWS

 2024 · Data Science: Deep Learning and Neural Networks in Python · Udemy

 2024 · Natural Language Processing with Deep Learning in Python · Udemy

 2024 · The Complete Node.js Developer Course · Udemy

 2024 · CyberSecurity · Udemy

 2023 · Networking Fundamentals · Udemy

 2022 · Data Structures & Algorithms · Udemy

 2022 · Docker & Kubernetes · Udemy

 2021 · Deep Learning Specialization · DeepLearning.AI

 2021 · Database Architecture, Scale and NoSQL with Elasticsearch · University of Michigan · Coursera

 2021 · Graph Theory · Udemy

 2021 · Configuring and Deploying VPCs with Multiple Subnets · AWS

 2021 · Introduction to Quantum Computing Course · IBM Quantum

 2021 · AWS Fundamentals Specialization · Amazon Web Services · Coursera

 2021 · Big Data: Hadoop and Spark · Udemy

 2021 · Master in Applied Statistics · Euroinnova Business School

 2021 · Full Stack development with Django · Udemy

 2021 · SQL: Data Reporting & Analysis · LinkedIn

 2020 · AI for Medical Diagnosis · Coursera

 2020 · Deep Learning with Keras · CGFIUBA

 2020 · Neural Networks & Deep Learning · Coursera

 2020 · Modern Deep Learning in Python · Deep Learning AI

 2020 · Recommender System and Deep Learning in Python · Udemy

 2020 · AWS Lambda & Serverless Architecture · Udemy

 2019 · ReactJS & Redux · Udemy

 2019 · Web Scraping with Python · Udemy

 2019 · Machine Learning with Python · Udemy

 2019 · Natural Language Processing with Python · Udemy

 2015 · IBM IT Specialist in Services and Infrastructure · IBM

 2010 · IBM AIX 5 Basics (Q1313) & Administration (Q1314) · IBM

AI Agents

 langchain-virtual-assistant: Engineered an AI-powered virtual assistant using LangChain and RAG, enabling context-aware conversations and document analysis with OpenAI's GPT models

 llm-react-api: Developed a full-stack React application with Node.js backend, integrating OpenAI's GPT API for intelligent content generation and React Flow for interactive data visualization

 sql-cursor-ai-agent: Built an intelligent SQL query builder using GPT-powered AI agents, enabling natural language to SQL conversion with React and Tailwind for an intuitive user interface

 langchain-agent-streamlit: Created an interactive LLM agent using LangChain and Streamlit, enabling natural language processing and decision-making capabilities with OpenAI integration

 gpt-context-injection: Engineered a context-aware GPT system implementing RAG techniques for enhanced response accuracy and domain-specific knowledge integration

Deep Learning

 higgs-boson-machine-learning: Developed advanced machine learning models to detect Higgs boson signals, utilizing scikit-learn for feature engineering and statistical analysis with comprehensive data visualization

 html2vec: Engineered a custom NLP pipeline to extract structured data from noisy HTML using SpaCy, Keras, and rule-based NER — deployed for semantic document indexing

 search-keras-gensim-elasticsearch: Built a semantic search engine combining Word Embeddings (GloVe) with Elasticsearch, enabling efficient text similarity search and content recommendation

 deep-age-classifier: Developed a CNN-based age detection system using Keras, implementing transfer learning for accurate facial age estimation with comprehensive data preprocessing

 keras-nltk-topic-modeling: Implemented neural network-based text classification using Keras and NLTK, enabling efficient topic modeling and document categorization

 keras-document-classifier: Built an asynchronous document classification system using Keras, integrating Google Search API for enhanced context and real-time processing

 python-recommender-systems: Created a fully serverless personalized recommendation engine with AWS Lambda, NumPy, and Algolia, delivering low-latency suggestions via collaborative filtering and novelty/diversity algorithms

 graph-link-prediction: Engineered a deep learning system for link prediction in graph networks using Keras, enabling accurate relationship forecasting in complex networks

 python-deep-learning-algorithms: Implemented advanced deep learning algorithms using Python, focusing on efficient numerical computing with NumPy and scientific computing with SciPy

 supply-chain-optimization: Engineered a supply chain optimization system using Python and NumPy, implementing efficient algorithms for logistics and resource allocation

 Python-Monte-Carlo-Simulator: Built a sophisticated Monte Carlo simulation framework using Python and SciPy, enabling complex probabilistic modeling and statistical analysis

 statistical-distributions: Developed a comprehensive statistical analysis toolkit using Python, implementing various probability distributions with SciPy and visualization with Matplotlib

 Genetic-Paper: Implemented genetic algorithms with focus on algorithmic complexity analysis, enabling efficient optimization and problem-solving strategies

Computer Vision

 opengl-samples: Developed a collection of OpenGL samples, enabling efficient 3D rendering and visualization with comprehensive documentation and examples

 image-classification-transformer: Implemented state-of-the-art image classification using Vision Transformers (ViT), achieving high accuracy with PyTorch and comprehensive visualization using Matplotlib and Seaborn

 keras-image-detection-classification: Developed a robust image detection and classification system using TensorFlow and Keras, implementing transfer learning for high-accuracy object recognition

 Python-Video-Processing: Developed a video generation system using MoviePy and OpenCV, enabling efficient video processing and manipulation

 media-tools: Built a video processing pipeline using FFMPEG, implementing efficient media conversion and manipulation through shell scripting

Data Engineering

 pyspark-docker: Containerized PySpark applications using Docker, enabling reproducible and scalable big data processing pipelines

 apache-hive-docker: Implemented containerized Hive data warehouse using Docker, enabling efficient SQL-like querying of large datasets

 hadoop-hdfs-map-reduce-docker: Containerized Hadoop ecosystem with MapReduce, enabling distributed processing of large-scale datasets in a reproducible environment

 hadoop-hdfs-kafka-docker: Deployed Kafka streaming platform with Hadoop integration using Docker, enabling real-time data processing and event streaming

 hadoop-hdfs-hbase-docker: Containerized HBase database with Hadoop integration, enabling scalable NoSQL storage and real-time data access

 sparkql: Developed efficient SparkSQL queries for big data processing, enabling complex data transformations and analytics

 pandas-geo-analytics: Developed geospatial data analytics using Pandas, enabling efficient processing and analysis of location-based data

 cross-datasource-entity-matching: Developed a robust entity matching system for cross-dataset integration, implementing efficient data alignment and validation techniques

DevOps

 aws-localstack-stream-processing: A fault-tolerant, batch-processed transaction signing pipeline using AWS Kinesis, S3, Aurora, and Secrets Manager with RSA encryption and exactly-once Lambda execution.

 aws-sagemaker-cdk: Engineered a production-grade MLOps infrastructure using AWS CDK, enabling scalable deployment and monitoring of multiple LLM models on SageMaker

 gcp-kubernetes: Deployed and managed Kubernetes clusters on GCP, implementing container orchestration and microservices architecture for scalable applications

 aws-django-ansible: Automated Django application deployment on AWS using Ansible and Terraform, implementing infrastructure as code and continuous deployment

 grpc-python: Implemented high-performance gRPC services in Python, enabling efficient microservices communication and streaming

 terraform-aws-django: Engineered infrastructure as code for Django applications on AWS using Terraform, enabling reproducible and scalable deployments

 aws-django-kubernetes: Deployed Django applications on AWS EKS, implementing container orchestration and microservices architecture

 aws-networking-elastic-beanstalk-automation: Automated AWS infrastructure setup including networking, RDS, ElastiCache, and Elasticsearch for scalable Django applications

 supervisor-python: Implemented process management for Python applications using Supervisord, ensuring reliable service operation and monitoring

 Python-Splunk-CLI: Developed Python integration with Splunk for log analysis and monitoring, enabling efficient log processing and visualization

 filesystem-tools: Engineered file system management tools with AWS S3 integration, enabling efficient cloud storage operations and automation

 development-tools: Created comprehensive development tools for Python, Android, TypeScript, Django, Git, and GPT integration

 python-jira-cli: Developed Python integration with JIRA, enabling automated issue tracking and project management

 web-to-pdf: Engineered web scraping tools using Python and Beautiful Soup, enabling efficient content extraction and PDF conversion

 python-web-crawler: Built an efficient web crawler in Python, implementing robust scraping and data extraction capabilities

Blockchain

 bitcoin-wallet-generator: Code for generating wallets that can store BTC without having to use a service like Blue Wallet or Electrum

 real-estate-solidity-contract: Developed secure and auditable real estate smart contracts in Solidity, implementing Merkle trees for efficient property verification

 solidity-upgradeable-contract: Engineered upgradeable smart contracts with advanced access control using OpenZeppelin, enabling secure and maintainable blockchain applications

 rust-alloy: Built a high-performance blockchain API using Rust, implementing async operations with Tokio and Warp, integrated with Alloy and Foundry for smart contract interaction

 zk-trust: Implemented zero-knowledge proof verification for ERC20 contracts, integrating with Etherscan and CoinMarketCap APIs for enhanced security

 zk-proof: Developed smart contracts with RISC Zero integration, enabling zero-knowledge proof verification for enhanced privacy and security

 anvil-of-fury: Created a local Ethereum development environment using Anvil, enabling efficient smart contract testing and deployment

 ethereum-solidity-contract: Engineered production-grade smart contracts for the Ethereum network, implementing secure and gas-efficient Solidity code

 django-multi-blockchain: Architected a cross-chain distributed system for Django, enabling seamless interaction with multiple blockchain networks

 solana-token-rust: Developed Solana token and NFT programs using Rust, implementing secure and efficient blockchain applications

 rust-ecopark: Built a high-performance database application in Rust, implementing efficient MySQL queries and Docker containerization

Backend

 python-fastapi: Engineered a high-performance REST API using FastAPI, implementing async operations and automatic OpenAPI documentation

 geo-django: Implemented geospatial applications using Django with PostGIS, enabling advanced location-based services and analytics

 hexagonal-spring-boot: Engineered a clean architecture application using Spring Boot and React, implementing hexagonal design patterns for maintainable code

 node-typescript-pdf-renderer: Built a PDF rendering service using TypeScript, enabling dynamic document generation and customization

 ai-syntax-compiler: Developed a custom programming language compiler for data scientists, implementing lexical analysis and parsing using Bison and Lex

 automata-python: Implemented various automata algorithms in Python, enabling efficient pattern matching and language processing

 java-spring-boot: Engineered enterprise applications using Spring Boot, implementing robust backend services and REST APIs

 data-structures-java: Implemented efficient data structures in Java, focusing on performance optimization and algorithm complexity

 django-data-analytics: Built a comprehensive data analytics platform using Django, implementing PnL, LTV, and retention analysis

 go-lang-app: Developed high-performance applications using Go, implementing concurrent processing and efficient resource utilization

 django-cms: Engineered a content management system using Django 3, implementing custom templates and forms for dynamic content

 flask-mongodb-celery-messaging-api: Built a scalable chat server using Flask, MongoDB, Redis, and Celery, enabling real-time messaging and asynchronous processing

 python-s3-media-server: Developed a file server using Flask and PIL, implementing efficient image processing and S3 storage integration

 python-chat-server-sockets: Engineered a real-time chat server using Python sockets, enabling efficient network communication and message handling

 Python-Google-Spreadsheets: Developed Python integration with Google Spreadsheets, enabling automated data processing and analysis

 software-patterns: Implemented various software design patterns in Python, demonstrating best practices for maintainable and scalable code

Frontend

 react-pnpm-workspaces: A monorepo template for sharing UI components between React web and React Native mobile apps using pnpm workspaces. Demonstrates platform-specific implementations with Vite, Expo, and TypeScript in a scalable architecture.

 microfrontends: Architected a distributed frontend system using microfrontends, enabling scalable and maintainable web applications for enterprise

 nextjs-app: Built a modern web application using Next.js, implementing server-side rendering and optimized performance

 vuejs-app: Developed a responsive web application using Vue.js and TypeScript, implementing component-based architecture

 svelte-app: Engineered a high-performance web application using Svelte, implementing reactive programming and efficient DOM updates

 react-typescript-app: Built a type-safe React application using TypeScript, implementing modern frontend development practices

 react-firebase-oauth: Developed a secure React application with Firebase OAuth 2.0 integration, enabling robust authentication and authorization

 flexbox-project: Implemented responsive layouts using CSS3 Flexbox, enabling modern and adaptive web design

 typescript-map-reduce: Engineered efficient data processing using TypeScript, implementing map-reduce patterns for large datasets

 typescript-mongodb-nestjs-mvc: Built a full-stack MVC application using TypeScript, MongoDB, and NestJS, implementing clean architecture principles

 typescript-classes: Implemented object-oriented programming patterns in TypeScript, demonstrating advanced class design and inheritance

Testing

 cypress-tests: Developed comprehensive end-to-end testing suite using Cypress, enabling reliable frontend testing and automation

 Flask-Application: Engineered a Flask REST API with 100% unit test coverage, implementing robust testing practices and continuous integration

 javascript-selenium-web-driver: Built automated testing framework using Selenium WebDriver, enabling comprehensive browser-based testing

Mobile

 Python-Android-Manager: Developed a web API for remote Android device emulator management, enabling efficient mobile testing and automation

 UNLaM-Android-App: Engineered a native Android calendar application, implementing efficient data management and user interface

Quantum Computing

 quantum-algorithms-java: Implemented quantum computing algorithms in Java, enabling efficient quantum circuit simulation and analysis

 assembly-logisim-circuits: Developed digital logic circuits using Logisim, implementing assembly language programming and circuit simulation

Books

 Agentic Design Patterns: A Hands-On Guide to Building Intelligent Systems by Antonio Gulli

 AWS Certified Machine Learning Engineer Study Guide: Associate by Dario Cabianca

 Official Google Cloud Certified Professional Machine Learning Engineer Study Guide by Mona Mona & Pratap Ramamurthy

 Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play by Jason Wei & Anjney Midha

 Learning OpenCV 4 Computer Vision with Python 3 by Joseph Howse & Joe Minichino

 Python Cookbook by David Beazley & Brian K. Jones

 Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann

 Building Microservices: Designing Fine-Granded Systems by Sam Newman

 Big Data: Principles and best practices of scalable realtime data by Nathan Marz & James Warren

 Data Analytics: Mide y Venceras by Inaki Gorostiza & Asier Barainca Fontao

 Técnicas de análisis de imagen: Aplicaciones en Biología by José F. Pertusa Grau

 Computer Networks by Andrew S. Tanenbaum & David J. Wetherall

 Historia de las telecomunicaciones by José Antonio Martín Pereda

 Applied Geospatial Data Science with Python: Leverage geospatial data analysis and modeling to find unique solutions to environmental problems by David S. Jordan

 UX Design by Pablo E. Fernández Casado

 Micro Frontends in Action by Michael Geers

 Transformers for Natural Language Processing and Computer Vision: Explore Generative AI and Large Language Models with Hugging Face, ChatGPT, GPT-4V, and DALL-E 3 by Denis Rothman

 The Model Thinker: What You Need to Know to Make Data Work for You by Scott E. Page

 Hands–On Machine Learning with Scikit–Learn and TensorFlow: Concepts, tools and techniques to build intelligent systems by Aurélien Géron

 Recommender Systems: The Textbook by Charu C. Aggarwal

 Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series) by Richard S. Sutton & Andrew G. Barto

 Practical Biostatistical Methods (Statistics) by Steve Selvin

 Modern Information Retrieval: The Concepts and Technology behind Search by Ricardo Baeza-Yates & Berthier Ribeiro-Neto

 Combinatorics: A Problem-Based Approach by Pavle Mladenoivc

 Técnicas de Optimización by Albert Corominas

 Logistic Regression by Barroso Utra, Isabel María & Luis Carlos Silva Ayçaguer

 Atomic Habits: Proven Builds and Break Habits by James Clear

 Influence: The Psychology of Persuasion by Robert B. Cialdini

 The Wolf of Wall Street: The Accidental Superhero of Finance by Jordan Belfort

 Never Eat Alone: And Other Secrets to Success, One Relationship at a Time by Keith Ferrazzi & Tahl Raz

 The Manager's Path: A Guide for Tech Leaders Navigating Growth and Change by Camille Fournier

 Slow Productivity: The Lost Art of Accomplishment Without Burnout by Cal Newport

 The Nuclear Effect: The 6 Pillars of Building a 7+ Figure Online Business by Scott Oldford

 Buy Back Your Time: Get Unstuck, Reclaim Your Freedom, and Build Your Empire by Dan Martell

 The Lean Startup by Eric Ries

 Zero to One: Notes on Startups, or How to Build the Future by Peter Thiel & Blake Masters

 Made to Stick: Why Some Ideas Survive and Others Die by Chip Heath & Dan Heath

 No Acting Please: The Art of Not Being a Dick by Eric Morris & Joan Hotchkis

 How to Win Friends & Influence People: The Only Book You Need to Lead You to Success by Dale Carnegie

 4 Hour Workweek: Escape 9-5, Live Anywhere, and Join the New Rich by Tim Ferriss

 $100M Offers: How To Make Offers So Good People Feel Stupid Saying No by Alex Hormozi

 Principles for Dealing with the Changing World Order: Why Nations Succeed or Fail by Ray Dalio

 Human Action: A treatise on economics by Ludwin Von Mises

 Other People's Money: Inside the Housing Crisis and the Demise of the Greatest Real Estate by Charles V. Bagli

 Matemáticas para la economía y las finanzas by Martin Anthony & Norman Biggs

 The Wealth of Nations by Adam Smith

 Debt: The First 5,000 Years by David Graeber

 12 Rules for Life: An Antidote to Chaos by Jordan Peterson

 12 New Rules for Life: Beyond Order by Jordan Peterson

 Quantum Computing In Action: A Java-based introduction by Johan Vos

 Shadows of the Mind: A Search for the Missing Science of Consciousness Reprint Edition by Roger Penrose

 Física by José Aguilar Peris, José Doria Rico, Juan de la Rubia Pacheco

 Schrodinger Equation by Daniel A. Fleisch

 The Body Electric: Electromagnetism And The Foundation Of Life by Robert O. Becker & Gary Selden

 Life on the Edge: The Coming of Age of Quantum Biology by Johnjoe McFadden & Jim Al-Khalili

 Activa tus mitocondrias: El secreto para una vida más longeva by Antonio Valenzuela

 The Wim Hof Method: Activate your potential by Wim Hof