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: Mentoring, Product Design, Code Review, Cross-functional, Roadmapping, Technical Decisions, Team Productivity, Conflict

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

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, BigQuery, 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, Cloud Monitoring, AWS API Gateway, RabbitMQ, Celery, GitLab CI, AWS CodePipeline, Kubernetes, AWS CloudWatch, Terraform, Pulumi, Shell, 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

Languages: Spanish, English

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.

I established a comprehensive mentorship program focused on knowledge transfer to engineering team members, translating complex business requirements into executable technical tasks. I 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 architected and implemented advanced LLM agents with OKR tracking and Computer Vision capabilities for automated document processing. I developed end-to-end pipelines for image-to-text data extraction using state-of-the-art models. I integrated multi-modal AI systems with business workflows for seamless automation. I utilized Model Context Protocol (MCP) and Google Agent Development Kit (ADK) for tool integrations and agent orchestration.

I led the design and deployment of scalable AI automation platforms, applying full-stack expertise in Django and React for production-grade systems. I engineered cloud infrastructure with business intelligence dashboards (Metabase) to drive operational insights.

I 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. I leveraged TypeScript for type safety and Tailwind CSS for rapid UI development, ensuring maintainable and scalable frontend architecture across multiple packages.

I 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. I orchestrated containerized applications using Google Kubernetes Engine for scalable microservices architecture. I established CI/CD pipelines and infrastructure automation for seamless deployments and scaling.

I built a comprehensive QA framework with Playwright for E2E testing and integrated monitoring solutions (DataDog, Sentry) for real-time observability and incident response. I implemented automated testing pipelines and established monitoring best practices for production systems.

I led a mixed-style team (high-autonomy builders and risk-focused reviewers) by setting clear interfaces, ownership boundaries, and decision logs—so execution stayed parallel and predictable.

I built a mentorship and knowledge-transfer program (pair programming, live-coding, bootcamps) to level up engineers with very different working styles and reduce onboarding time.

I turned ‘what could go wrong’ concerns into concrete mitigations (tests, monitoring, rollout plans), reducing incidents while maintaining shipping cadence.

I achieved a 40% reduction in onboarding time for new engineers and increased team velocity by 25% within 6 months through structured knowledge transfer.

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.

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.

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.

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.

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: Mentorship, Knowledge Transfer, Product Requirements, Technical Leadership, Live-coding, Pair-programming, Technical Workshops, OKR, LLM Agents, Computer Vision, OCR, Document Processing, Multi-modal AI, Data Extraction, Image Processing, LangChain, Google Agents SDK, OpenAI Agents SDK, Pytorch, TensorFlow, MCP, Google ADK, Django, React, AI Agents, Metabase, React, PNPM, Monorepo, Zustand, React Query, Axios, TypeScript, Tailwind, Pulumi, Cloud Run, GKE, Kubernetes, Cloud SQL, Redis, Google Cloud Monitoring, CI/CD, Infrastructure as Code (IaC), Google Cloud Platform (GCP), Playwright, Sentry, DataDog, E2E, Cloud Monitoring, Incident Management, Automated Tests

2022 - 2024 · Blockchain Engineer · Makersplace

San Francisco, US

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

I built end-to-end digital asset infrastructure integrating Django backends with Solidity smart contracts and Rust-based logic for Web3 protocols. I led NFT and phygital asset deployments using web3.js, Alchemy, and IPFS, integrating smart contracts with full-stack applications. I partnered with cross-functional teams (marketing, sales) to launch blockchain-based digital campaigns that increased user engagement and retention.

I diagnosed and resolved critical failures in blockchain workflows, including transaction validation, IPFS metadata syncing, and dynamic gas optimization. I designed fault-tolerant microservices for real-time blockchain transaction monitoring and distributed data pipelines.

I developed production-grade MLOps pipeline on AWS for scalable model lifecycle management, leveraging Docker, Kubernetes, and SageMaker. I enabled model versioning and continuous monitoring for production ML workflows, ensuring data drift detection and model rollback.

I automated deployment infrastructure using AWS CDK and CI/CD pipelines (GitHub Actions, Elastic Beanstalk, ECR), achieving zero-downtime rollouts. I dockerized applications and managed deployment environments using Elastic Beanstalk, ECR, RDS, and Opensearch.

I directed enterprise-scale data migration to GCP BigQuery, optimizing ETL pipelines with Data Fusion for low-latency analytics. I enabled real-time data access for business intelligence.

I built full-spectrum test automation suite with Cypress, PyTest, and integration testing frameworks — enforced zero-regression policies pre-launch. I validated digital drops and NFT-related product features to ensure high quality and zero regression.

I delivered under aggressive launch timelines by making explicit tradeoffs (guardrails, rollback plans, monitoring) that protected reliability while meeting drop deadlines.

I partnered cross-functionally (marketing/sales + engineering) to ship blockchain features fast, while keeping transaction integrity high through automation and fault-tolerant services.

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.

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.

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.

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.

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.

I increased test coverage from 45% to 92% and reduced regression bugs in production by 85% through comprehensive automated testing.

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

2020 - 2022 · Data Engineer · Rings AI

San Francisco, US

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

I architected and developed a custom CRM platform designed to improve outreach effectiveness using AI-driven insights from network relationship data. I implemented intelligent dataset enrichment by integrating multiple external data sources, enabling personalized outreach strategies and opportunity intelligence. I built machine learning models to analyze relationship patterns and predict optimal engagement approaches. I integrated computer vision capabilities for automated profile image analysis and document processing to enhance contact data quality.

I built real-time distributed graph algorithm in Spark for relationship path analysis. I streamlined data materialization using AWS Glue, SQS, and ETL processes.

I designed high-throughput serverless backend using AWS Lambda, event-driven SQS/SNS queues, and Elasticsearch for log indexing and traceability. I ensured high availability and scalability across the architecture.

I constructed scalable ETL pipelines using AWS Glue and Athena to support Redshift-based data warehousing and interactive querying. I improved data warehouse performance and reporting efficiency.

I optimized cloud network infrastructure with custom VPC architectures, reducing inter-zone data transfer costs by 30% via NAT gateway tuning. I reduced data transfer costs while ensuring security.

I integrated secure authentication and audit logging using AWS Cognito, Google OAuth 2.0, and serverless event-driven Lambda functions. I ensured compliance and traceability.

I implemented micro-frontends in React with GraphQL over AWS AppSync to support real-time UI rendering and scalable user data interactions. I integrated robust data flows using Node and TypeScript.

I created automated QA pipelines with Cypress, GitHub Actions, and Slack alerts to ensure continuous delivery and rapid feedback loops. I managed CI/CD workflows to maintain code quality.

I performed production diagnostics using AWS observability stack (CloudWatch, X-Ray, custom metrics), producing detailed RCA reports. I delivered actionable RCA reports and fixes.

I worked in Agile teams using Scrum, Jira, and Confluence. I optimized sprint velocity and stakeholder communication.

I built probabilistic matching algorithms using AWS Glue and distributed lookups. I enhanced data integration across sources.

I deployed secure CDN with Lambda@Edge and CloudFront. I reduced latency and improved user content delivery.

I applied cost tags and managed resources with AWS Organizations. I enhanced budget accountability and forecast accuracy.

I collaborated effectively with very direct, high-bar engineers by focusing on evidence: benchmarks, RFCs, and reproducible experiments—turning sharp debate into better architecture.

I navigated high-stakes stakeholder pressure by documenting tradeoffs, defining objective success metrics, and protecting delivery from last-minute churn.

I increased outreach conversion rates by 65% and reduced data enrichment time from 2 hours to 15 minutes per contact through AI-powered automation.

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.

I achieved 99.95% uptime and reduced infrastructure costs by 60% compared to traditional EC2-based architecture while handling 10x traffic spikes.

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.

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.

I reduced authentication failures by 80% and achieved 100% audit trail coverage for all user actions, ensuring full compliance with security requirements.

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.

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.

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.

I increased team sprint velocity by 35% and reduced sprint planning time by 50% through improved Agile practices and streamlined communication workflows.

I improved entity matching accuracy from 82% to 96% and reduced processing time by 65% through optimized probabilistic algorithms and distributed processing.

I reduced content delivery latency by 60% (from 800ms to 320ms) and decreased CDN costs by 40% through optimized caching strategies and edge computing.

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

2019 - 2020 · Full-Stack Engineer · ConCntric

San Francisco, US

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

I designed and deployed distributed data pipelines using Python and AWS Serverless architecture. I integrated observability, unit testing, CI/CD pipelines, and Slack alerts for end-to-end monitoring and traceability.

I implemented a Lambda-based recommendation engine with collaborative filtering and model evaluation via NRMSE and novelty metrics. I integrated Algolia for search indexing and relevance tuning.

I designed an end-to-end NLP system to extract structured data from semi-structured HTML using SpaCy, Keras, and regex parsing. I employed SpaCy, Keras, and AWS Comprehend to support data classification, entity recognition, and semantic search.

I built and deployed an interactive React marketplace frontend with Redux, Saga, and Stripe Connect. I enabled seamless payments, authentication, and real-time notifications via Firebase and AWS Amplify.

I boosted runtime efficiency by refactoring Python data pipelines with Cython acceleration and asynchronous programming patterns. I leveraged profiling tools and migrated to compiled modules to boost efficiency across pipelines.

I created automated QA pipelines with Cypress, GitHub Actions, and Slack alerts to ensure continuous delivery and rapid feedback loops. I implemented data quality acceptance checks to prevent drift and maintain ML model accuracy.

I operated as a "bridge" engineer, translating data science proofs-of-concept into production-ready microservices that the rest of the team could support.

I advocated for better observability across the stack, turning "it feels slow" complaints into measurable latency charts and targeted fixes.

I reduced pipeline execution time by 50% (from 4 hours to 2 hours) and achieved 99.9% reliability through serverless architecture and comprehensive monitoring.

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.

I improved data extraction accuracy from 72% to 91% and reduced processing time by 70% through optimized NLP pipelines and entity recognition models.

I increased transaction completion rate by 38% and reduced payment processing errors by 85% through optimized payment flows and real-time error handling.

I improved pipeline performance by 5x (from 2 hours to 24 minutes) and reduced memory usage by 40% through Cython optimization and asynchronous processing.

I increased test coverage from 55% to 90% and reduced production bugs by 75% through comprehensive automated testing and data quality checks.

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

2016 - 2019 · Growth Engineer · Ampush

San Francisco, US

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

I engineered experimentation and user analytics backend in Flask with scalable AWS integration — enabled granular A/B testing and real-time metrics. I designed backend reporting APIs and implemented exception handling and i18n features across distributed services.

I collaborated with global engineering teams using Agile methods (Scrum, Kanban, Sprints). I participated in code reviews, pull requests, and documentation using Jira and Confluence.

I built scalable analytics backend using Flask APIs and AWS stack (Lambda, EC2, RDS), enabling real-time data access and reporting. I enabled secure and scalable data workflows.

I led transition from monolith to microservices using AWS ECS, SQS, and Docker. Focused on fault tolerance, eventual consistency, and clean architectural principles.

I architected hybrid storage systems with PostgreSQL, Cassandra, DynamoDB, and Elasticsearch for real-time querying and NoSQL/relational workloads. I used DBT for data transformations and NoSQL architecture.

I strengthened software quality with automated tests, CI pipelines, and fault-monitoring tools like Sentry and Splunk. I enhanced reliability across microservices.

I integrated multi-channel attribution APIs (Google Ads, Facebook, AppsFlyer) to unify performance tracking across ad platforms with Tableau dashboards. I collaborated with business stakeholders to optimize customer LTV, RPA, and CPA through analytics dashboards and ad performance APIs.

I built secure microservices payment infrastructure with Stripe and Shopify APIs, managing compliance, tokenization, and recurring billing. I managed subscriptions, refunds, compliance, and tokenized transactions securely.

I created automated QA pipelines with Cypress, GitHub Actions, and Slack alerts to ensure continuous delivery and rapid feedback loops. I ensured application stability post-deployment with CI workflows and monitoring.

I navigated significant time-zone differences (SF vs. remote teams) by adopting asynchronous communication flows (RFCs, documented handoffs) that kept velocity high.

I acted as the 'glue' between product requests and engineering reality, often negotiating scope down to MVP to meet marketing campaign deadlines.

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.

I improved team productivity by 30% and reduced sprint planning overhead by 40% through optimized Agile workflows and cross-team collaboration.

I reduced infrastructure costs by 50% and improved system scalability to handle 10x traffic growth through optimized AWS architecture and auto-scaling strategies.

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.

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.

I increased test coverage from 40% to 85% and reduced production incidents by 80% through comprehensive automated testing and proactive monitoring.

I improved customer LTV by 25% and reduced CPA by 30% through data-driven attribution modeling and real-time analytics dashboards.

I reduced payment processing failures by 90% and improved transaction security compliance to 100% through secure tokenization and comprehensive compliance checks.

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: Python, Flask, REST API, Python-Flask-Restful, Flask-Restless, OpenPyXL, boto3, multi-threading, Python3 Eggs, Exception Handling, Error Codes, i18n & l18n, Sprints, Scrum, Kanban, Documentation, JIRA, Confluence, Pull Requests, Code Reviews, AWS EC2, AWS Elastic Beanstalk, AWS Route 53, AWS DynamoDB, AWS RDS, AWS S3, AWS Lambda, AWS SES, AWS SimpleDB, AWS ECS, AWS SQS, AWS SNS, Docker, HashCorp Consul, Eventual Consistency, Fault Tolerance, Idempotence Principle, Single Responsability Principle, Independence Principle, Apacha Cassandra, Elasticsearch, AWS DynamoDB, PostgreSQL, AWS RDS, DBT, NoSQL, Unit Tests, Integration Tests, Stress Tests, Longevity Tests, CircleCI, Rollbar, Sentry, Splunk, AWS CloudWatch Alerts, Fault Tolerance Analysis, SQL, Google Adwords API, Google Analytics API, Facebook Marketing API, Facebook Messenger API, AppsFlyer API, Outbrain API, Yahoo Gemini API, Tableau, Knowi, Mailchimp API, Spend, Impressions, Clicks, Conversion Rate, RPA, CPA, LTV, Retention, A/B Testing, Shopify API, ReCharge Payments API, Stripe API, Online Payments Processing, Credit Card Tokenization, Compliance, Charges Management, Subscription Management, Refund Policy, E2E, GitHub Actions, Slack Alerts, Feedback Loops, CD, Rollbar, Sentry, Splunk, AWS CloudWatch Alerts, Stability

2010 - 2016 · Certified IT Specialist · IBM

Buenos Aires, Argentina

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

I provided UNIX system administration for global banking clients, managing RHEL, AIX, and Solaris systems. I automated tasks using Bash and KSH scripting.

I led successful data center migration for American Express. I handled incident, patch, and disaster recovery procedures using ITSM tools like Service Now and BMC Remedy. I provided English-language customer support for American Express customers.

I configured and managed core networking services (DNS, DHCP, LDAP, SSL). I diagnosed connectivity issues using netstat, traceroute, and nmap.

I provisioned and managed storage using SAN, NAS, GPFS, and volume managers. I enabled high availability for banking workloads.

I developed and maintained server automation scripts using Python, Perl, and Shell scripting for infrastructure management. I created ETL jobs and automated deployment processes to streamline operations for enterprise banking clients.

I built internal LAMP web applications and tools using Java Spring Boot, PHP, and Django. I implemented modular components with design patterns, created responsive frontends with HTML, CSS, jQuery, and Bootstrap for enterprise dashboards.

I administered Oracle, DB2, MySQL, and MongoDB databases. I ensured high availability and consistent backups.

I managed observability for 1,000+ distributed nodes using custom metrics, Sentry, and AWS CloudWatch — improved MTTR and system resilience. I improved service reliability and early issue detection.

I standardized operations across diverse legacy systems by documenting runbooks and scripts, reducing dependency on 'hero' engineers.

I trained junior admins to handle routine alerts and patches, freeing up senior staff for complex migrations.

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.

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.

I reduced network-related incidents by 70% and improved DNS resolution time by 40% through optimized network configuration and proactive monitoring.

I improved storage utilization from 65% to 85% and reduced storage-related downtime by 90% through optimized provisioning and high-availability configurations.

I reduced manual server management time by 75% and improved deployment consistency from 85% to 98% through comprehensive automation scripts.

I reduced application development time by 40% and improved code reusability by 60% through modular design patterns and component-based architecture.

I improved database performance by 35% and achieved 100% backup success rate with zero data loss through optimized database configurations and automated backup strategies.

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

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