Martín Alejandro Castro Álvarez
Software Engineer
Martín Alejandro Castro Álvarez, Software Engineer
martincastro.10.5@gmail.com
https://martincastroalvarez.com
https://github.com/MartinCastroAlvarez
https://www.linkedin.com/in/martincastroalvarez/
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
Skills
Team Leadership
Architecture Design
Backend Development
Frontend Development
Blockchain & Web3
Data Engineering & Analytics
DevOps & Infrastructure
AI & Machine Learning
Testing & Quality Assurance
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Built real-time distributed graph algorithm in Spark for relationship path analysis. Streamlined data materialization using AWS Glue, SQS, and ETL processes.
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.
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.
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.
Integrated secure authentication and audit logging using AWS Cognito, Google OAuth 2.0, and serverless event-driven Lambda functions. Ensured compliance and traceability.
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.
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.
Performed production diagnostics using AWS observability stack (CloudWatch, X-Ray, custom metrics), producing detailed RCA reports. Delivered actionable RCA reports and fixes.
Worked in Agile teams using Scrum, Jira, and Confluence. Optimized sprint velocity and stakeholder communication.
Built probabilistic matching algorithms using AWS Glue and distributed lookups. Enhanced data integration across sources.
Deployed secure CDN with Lambda@Edge and CloudFront. Reduced latency and improved user content delivery.
Applied cost tags and managed resources with AWS Organizations. Enhanced budget accountability and forecast accuracy.
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.
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.
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.
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.
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.
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.
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.
Collaborated with global engineering teams using Agile methods (Scrum, Kanban, Sprints). Participated in code reviews, pull requests, and documentation using Jira and Confluence.
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.
Led transition from monolith to microservices using AWS ECS, SQS, and Docker. Focused on fault tolerance, eventual consistency, and clean architectural principles.
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.
Strengthened software quality with automated tests, CI pipelines, and fault-monitoring tools like Sentry and Splunk. Enhanced reliability across microservices.
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.
Built secure microservices payment infrastructure with Stripe and Shopify APIs, managing compliance, tokenization, and recurring billing. Managed subscriptions, refunds, compliance, and tokenized transactions securely.
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.
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.
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.
Configured and managed core networking services (DNS, DHCP, LDAP, SSL). Diagnosed connectivity issues using netstat, traceroute, and nmap.
Provisioned and managed storage using SAN, NAS, GPFS, and volume managers. Enabled high availability for banking workloads.
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.
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.
Administered Oracle, DB2, MySQL, and MongoDB databases. Ensured high availability and consistent backups.
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.
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
Experience
2024 - Today
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.
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.
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.
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.
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.
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.
2022 - 2024
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.
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.
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.
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.
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.
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.
2020 - 2022
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.
Built real-time distributed graph algorithm in Spark for relationship path analysis. Streamlined data materialization using AWS Glue, SQS, and ETL processes.
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.
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.
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.
Integrated secure authentication and audit logging using AWS Cognito, Google OAuth 2.0, and serverless event-driven Lambda functions. Ensured compliance and traceability.
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.
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.
Performed production diagnostics using AWS observability stack (CloudWatch, X-Ray, custom metrics), producing detailed RCA reports. Delivered actionable RCA reports and fixes.
Worked in Agile teams using Scrum, Jira, and Confluence. Optimized sprint velocity and stakeholder communication.
Built probabilistic matching algorithms using AWS Glue and distributed lookups. Enhanced data integration across sources.
Deployed secure CDN with Lambda@Edge and CloudFront. Reduced latency and improved user content delivery.
Applied cost tags and managed resources with AWS Organizations. Enhanced budget accountability and forecast accuracy.
2019 - 2020
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.
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.
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.
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.
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.
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.
2016 - 2019
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.
Collaborated with global engineering teams using Agile methods (Scrum, Kanban, Sprints). Participated in code reviews, pull requests, and documentation using Jira and Confluence.
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.
Led transition from monolith to microservices using AWS ECS, SQS, and Docker. Focused on fault tolerance, eventual consistency, and clean architectural principles.
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.
Strengthened software quality with automated tests, CI pipelines, and fault-monitoring tools like Sentry and Splunk. Enhanced reliability across microservices.
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.
Built secure microservices payment infrastructure with Stripe and Shopify APIs, managing compliance, tokenization, and recurring billing. Managed subscriptions, refunds, compliance, and tokenized transactions securely.
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.
2010 - 2016
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.
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.
Configured and managed core networking services (DNS, DHCP, LDAP, SSL). Diagnosed connectivity issues using netstat, traceroute, and nmap.
Provisioned and managed storage using SAN, NAS, GPFS, and volume managers. Enabled high availability for banking workloads.
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.
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.
Administered Oracle, DB2, MySQL, and MongoDB databases. Ensured high availability and consistent backups.
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.
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
Education
Certifications
2025
2024
2024
2023
2022
2022
2021
2021
2021
2021
2021
2021
2021
2021
2020
2020
2020
2020
2020
2019
2019
2019
2015
2010
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
Deep Learning
Engineered an AI-powered virtual assistant using LangChain and RAG, enabling context-aware conversations and document analysis with OpenAI's GPT models
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
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
Developed advanced machine learning models to detect Higgs boson signals, utilizing scikit-learn for feature engineering and statistical analysis with comprehensive data visualization
Created an interactive LLM agent using LangChain and Streamlit, enabling natural language processing and decision-making capabilities with OpenAI integration
Engineered a context-aware GPT system implementing RAG techniques for enhanced response accuracy and domain-specific knowledge integration
Engineered a custom NLP pipeline to extract structured data from noisy HTML using SpaCy, Keras, and rule-based NER — deployed for semantic document indexing
Built a semantic search engine combining Word Embeddings (GloVe) with Elasticsearch, enabling efficient text similarity search and content recommendation
Developed a CNN-based age detection system using Keras, implementing transfer learning for accurate facial age estimation with comprehensive data preprocessing
Implemented neural network-based text classification using Keras and NLTK, enabling efficient topic modeling and document categorization
Built an asynchronous document classification system using Keras, integrating Google Search API for enhanced context and real-time processing
Created a fully serverless personalized recommendation engine with AWS Lambda, NumPy, and Algolia, delivering low-latency suggestions via collaborative filtering and novelty/diversity algorithms
Engineered a deep learning system for link prediction in graph networks using Keras, enabling accurate relationship forecasting in complex networks
Implemented advanced deep learning algorithms using Python, focusing on efficient numerical computing with NumPy and scientific computing with SciPy
Developed a robust entity matching system for cross-dataset integration, implementing efficient data alignment and validation techniques
Engineered a supply chain optimization system using Python and NumPy, implementing efficient algorithms for logistics and resource allocation
Built a sophisticated Monte Carlo simulation framework using Python and SciPy, enabling complex probabilistic modeling and statistical analysis
Developed a comprehensive statistical analysis toolkit using Python, implementing various probability distributions with SciPy and visualization with Matplotlib
Implemented genetic algorithms with focus on algorithmic complexity analysis, enabling efficient optimization and problem-solving strategies
Computer Vision
Developed a collection of OpenGL samples, enabling efficient 3D rendering and visualization with comprehensive documentation and examples
Implemented state-of-the-art image classification using Vision Transformers (ViT), achieving high accuracy with PyTorch and comprehensive visualization using Matplotlib and Seaborn
Developed a robust image detection and classification system using TensorFlow and Keras, implementing transfer learning for high-accuracy object recognition
Cloud Infrastructure
A fault-tolerant, batch-processed transaction signing pipeline using AWS Kinesis, S3, Aurora, and Secrets Manager with RSA encryption and exactly-once Lambda execution.
Engineered a production-grade MLOps infrastructure using AWS CDK, enabling scalable deployment and monitoring of multiple LLM models on SageMaker
Deployed and managed Kubernetes clusters on GCP, implementing container orchestration and microservices architecture for scalable applications
Containerized PySpark applications using Docker, enabling reproducible and scalable big data processing pipelines
Implemented containerized Hive data warehouse using Docker, enabling efficient SQL-like querying of large datasets
Containerized Hadoop ecosystem with MapReduce, enabling distributed processing of large-scale datasets in a reproducible environment
Deployed Kafka streaming platform with Hadoop integration using Docker, enabling real-time data processing and event streaming
Containerized HBase database with Hadoop integration, enabling scalable NoSQL storage and real-time data access
Developed efficient SparkSQL queries for big data processing, enabling complex data transformations and analytics
Automated Django application deployment on AWS using Ansible and Terraform, implementing infrastructure as code and continuous deployment
Implemented high-performance gRPC services in Python, enabling efficient microservices communication and streaming
Engineered infrastructure as code for Django applications on AWS using Terraform, enabling reproducible and scalable deployments
Deployed Django applications on AWS EKS, implementing container orchestration and microservices architecture
Automated AWS infrastructure setup including networking, RDS, ElastiCache, and Elasticsearch for scalable Django applications
Implemented process management for Python applications using Supervisord, ensuring reliable service operation and monitoring
Developed Python integration with Splunk for log analysis and monitoring, enabling efficient log processing and visualization
Engineered file system management tools with AWS S3 integration, enabling efficient cloud storage operations and automation
Blockchain
Code for generating wallets that can store BTC without having to use a service like Blue Wallet or Electrum
Developed secure and auditable real estate smart contracts in Solidity, implementing Merkle trees for efficient property verification
Engineered upgradeable smart contracts with advanced access control using OpenZeppelin, enabling secure and maintainable blockchain applications
Built a high-performance blockchain API using Rust, implementing async operations with Tokio and Warp, integrated with Alloy and Foundry for smart contract interaction
Implemented zero-knowledge proof verification for ERC20 contracts, integrating with Etherscan and CoinMarketCap APIs for enhanced security
Developed smart contracts with RISC Zero integration, enabling zero-knowledge proof verification for enhanced privacy and security
Created a local Ethereum development environment using Anvil, enabling efficient smart contract testing and deployment
Engineered production-grade smart contracts for the Ethereum network, implementing secure and gas-efficient Solidity code
Architected a cross-chain distributed system for Django, enabling seamless interaction with multiple blockchain networks
Developed Solana token and NFT programs using Rust, implementing secure and efficient blockchain applications
Built a high-performance database application in Rust, implementing efficient MySQL queries and Docker containerization
Backend
Engineered a high-performance REST API using FastAPI, implementing async operations and automatic OpenAPI documentation
Developed a video generation system using MoviePy and OpenCV, enabling efficient video processing and manipulation
Built a video processing pipeline using FFMPEG, implementing efficient media conversion and manipulation through shell scripting
Implemented geospatial applications using Django with PostGIS, enabling advanced location-based services and analytics
Developed geospatial data analytics using Pandas, enabling efficient processing and analysis of location-based data
Engineered a clean architecture application using Spring Boot and React, implementing hexagonal design patterns for maintainable code
Built a PDF rendering service using TypeScript, enabling dynamic document generation and customization
Developed a custom programming language compiler for data scientists, implementing lexical analysis and parsing using Bison and Lex
Implemented various automata algorithms in Python, enabling efficient pattern matching and language processing
Engineered enterprise applications using Spring Boot, implementing robust backend services and REST APIs
Implemented efficient data structures in Java, focusing on performance optimization and algorithm complexity
Built a comprehensive data analytics platform using Django, implementing PnL, LTV, and retention analysis
Developed high-performance applications using Go, implementing concurrent processing and efficient resource utilization
Engineered a content management system using Django 3, implementing custom templates and forms for dynamic content
Built a scalable chat server using Flask, MongoDB, Redis, and Celery, enabling real-time messaging and asynchronous processing
Developed a file server using Flask and PIL, implementing efficient image processing and S3 storage integration
Engineered a real-time chat server using Python sockets, enabling efficient network communication and message handling
Built an efficient web crawler in Python, implementing robust scraping and data extraction capabilities
Developed Python integration with Google Spreadsheets, enabling automated data processing and analysis
Implemented various software design patterns in Python, demonstrating best practices for maintainable and scalable code
Engineered web scraping tools using Python and Beautiful Soup, enabling efficient content extraction and PDF conversion
Created comprehensive development tools for Python, Android, TypeScript, Django, Git, and GPT integration
Developed Python integration with JIRA, enabling automated issue tracking and project management
Frontend
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.
Architected a distributed frontend system using microfrontends, enabling scalable and maintainable web applications for enterprise
Built a modern web application using Next.js, implementing server-side rendering and optimized performance
Developed a responsive web application using Vue.js and TypeScript, implementing component-based architecture
Engineered a high-performance web application using Svelte, implementing reactive programming and efficient DOM updates
Built a type-safe React application using TypeScript, implementing modern frontend development practices
Developed a secure React application with Firebase OAuth 2.0 integration, enabling robust authentication and authorization
Implemented responsive layouts using CSS3 Flexbox, enabling modern and adaptive web design
Engineered efficient data processing using TypeScript, implementing map-reduce patterns for large datasets
Built a full-stack MVC application using TypeScript, MongoDB, and NestJS, implementing clean architecture principles
Implemented object-oriented programming patterns in TypeScript, demonstrating advanced class design and inheritance
Testing
Developed comprehensive end-to-end testing suite using Cypress, enabling reliable frontend testing and automation
Engineered a Flask REST API with 100% unit test coverage, implementing robust testing practices and continuous integration
Built automated testing framework using Selenium WebDriver, enabling comprehensive browser-based testing
Mobile
Developed a web API for remote Android device emulator management, enabling efficient mobile testing and automation
Engineered a native Android calendar application, implementing efficient data management and user interface
Quantum Computing
Implemented quantum computing algorithms in Java, enabling efficient quantum circuit simulation and analysis
Developed digital logic circuits using Logisim, implementing assembly language programming and circuit simulation
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