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Igor Lourenço dos Santos

Palmas, Brazil

igorlourenco.dev@gmail.com • LinkedIn • Github

Summary

AI Engineer with 8+ years of software development experience and a strong pivot into production AI systems, intelligent document processing, and workflow automation. Built and deployed AI-powered document analysis pipelines using LLMs, RAG architectures, and structured prompt engineering, serving 50+ users in production. Deep backend expertise in Python, TypeScript, and Node.js with hands-on experience designing data pipelines, real-time processing systems, and scalable cloud infrastructure on AWS. Proven ability to ship production-grade systems in regulated, compliance-sensitive environments. Startup-native engineer who thrives in lean, high-performing teams with full ownership from architecture through deployment.

Experiences

  • BUCKSENSE INC | Senior AI/Full-Stack Engineer | Mar 2023 - Present | New York, NY (Remote)

    • Designed and deployed intelligent automation workflows integrating AI-driven content management, analytics pipelines, and automated decision routing for 20+ enterprise clients, reducing manual processing by 60% and improving operational efficiency by 3x;
    • Built production data pipelines ingesting multi-source analytics data (Google Analytics, CMS, custom metrics) with automated quality checks and monitoring, surfacing actionable insights on conversion funnels that informed $10M+ optimization strategy;
    • Led cross-functional team of 6 engineers to deliver enterprise platform 2 weeks ahead of schedule, facilitating $10M+ monthly transactions; operated with high agency to identify bottlenecks, propose architectural improvements, and drive consensus on data-driven redesigns;
    • Architected modular component and service library used across 3 client projects, reducing feature development time by 60%. Shipped 15+ features in 6 months with zero production incidents;
    • Designed, deployed, and maintained scalable cloud infrastructure on AWS (Lambda, S3, DynamoDB, ECS) with 99.9% uptime, implementing CI/CD pipelines and automated monitoring.

  • DRIP TRADE | Senior Engineer, AI and Automation | Jan 2024 - Aug 2024 | Miami, FL (Remote)

    • Architected intelligent admin portal processing 10K+ financial asset listings with automated classification, transaction monitoring, and anomaly detection. Enabled operations team to handle compliance review 5x faster than previous manual workflows;
    • Built real-time analytics dashboard with automated data quality monitoring, visualizing transaction flows, engagement metrics, and platform health indicators. Provided executive team with actionable intelligence that informed product roadmap;
    • Designed intelligent routing system for transaction processing, auto-approving standard operations and escalating complex cases to human reviewers, reducing average processing time by 40%;
    • Implemented extensive error handling, logging, and monitoring pipelines ensuring data integrity and audit compliance across all platform operations.

  • RHIZOM TECNOLOGIA | AI/Backend Engineer | Mar 2022 - Mar 2023 | Santa Catarina, Brazil (Remote)

    • Architected and launched multi-chain financial platform processing $2M+ in transaction volume, onboarding 5K+ users in first 3 months with 99.9% transaction success rate. Designed compliance-aligned validation workflows ensuring regulatory adherence;
    • Engineered 8+ production-grade smart contracts with comprehensive security audits; optimized processing efficiency by 40% through algorithmic optimization and achieved zero vulnerabilities post-audit;
    • Built scalable backend integration layer with real-time event processing, transaction validation, and sub-second latency monitoring. Implemented automated data quality checks and alerting systems;
    • Partnered with Engineering leadership to define technical roadmap and expansion strategy; mentored 3 junior developers, reducing onboarding time from 8 to 3 weeks.

  • POPSTAND | Backend/Data Engineer | Dec 2021 - Mar 2022 | San Francisco, CA (Remote)

    • Engineered cross-chain data aggregation pipeline processing financial asset data across multiple sources via REST APIs, enabling real-time portfolio valuation tracking $50M+ in holdings for 10K+ users with 99.5% API uptime;
    • Built RESTful API backend in Python and Node.js handling 100K+ daily requests with Redis caching and MongoDB; implemented WebSocket connections for real-time data streaming, reducing data latency from 5s to <500ms;
    • Designed automated data ingestion and quality monitoring pipelines ensuring data consistency, completeness, and accuracy across multi-source financial datasets;
    • Mentored 2 junior engineers in backend architecture, data pipeline design, and production best practices.

  • FOTON TECH | Full-Stack Engineer, AI Integration | Jan 2021 - Aug 2021 | São Paulo, Brazil (Remote)

    • Developed and launched production platform (Python, TypeScript, AWS Lambda, DynamoDB, S3) achieving 50K+ users; architected serverless backend with real-time messaging and event-driven data processing;
    • Led end-to-end CI/CD automation pipeline (GitHub Actions) that reduced release cycle from 3 days to 4 hours with zero critical bugs across 20+ releases;
    • Spearheaded backend modernization migrating legacy systems to modern Python/TypeScript stack, implementing automated testing, monitoring, and 40% performance improvement;
    • Led 4-person team partnering directly with C-suite executives to define product roadmap and translate business requirements into technical specifications for AI-enhanced features.

Projects

  • AI DOCUMENT ANALYSIS PIPELINE | Personal Project | 2025 | Live Project
    • Built production AI system for automated PDF document analysis with intelligent document processing. Ingests financial and regulatory documents, extracts key findings, maps evidence to claims, and generates structured compliance reports. Used by 50+ users, reducing manual document review time by 90%;
    • Architected RAG pipeline with real-time streaming analysis, structured output parsing, and multi-dimensional evaluation using LLM APIs (Anthropic Claude, Google Gemini);
    • Engineered prompt optimization framework following Anthropic's prompt engineering methodology, achieving 85% analysis accuracy on complex regulatory documents;
    • Implemented automated data quality checks, document validation, and error handling ensuring production reliability;
    • Tech Stack: Python, TypeScript, LangChain, RAG, Anthropic Claude API, Google Gemini API, Vercel AI SDK, PDF processing, Next.js.

Technical Skills

  • AI/ML Engineering: LangChain, LangGraph, RAG Pipelines, Prompt Engineering, Intelligent Document Processing, Workflow Automation, OpenAI API, Anthropic Claude API, Google Gemini API, Vercel AI SDK, TensorFlow, PyTorch, Scikit-Learn;
  • Backend and Data: Python, Node.js, Express.js, REST APIs, GraphQL, WebSocket, PostgreSQL, MongoDB, Redis, Data Pipelines, Apache Kafka, Apache Airflow, n8n;
  • Cloud Infrastructure: AWS (Lambda, S3, DynamoDB, ECS, CDK, Amplify), Docker, CI/CD (GitHub Actions), Automated Monitoring, Serverless Architecture;
  • Programming Languages: Python, TypeScript, JavaScript, SQL, Rust, Solidity;
  • Domain Expertise: Fintech, Regulated Industries, Compliance-First Design, Financial Data Processing, Audit Systems;
  • Languages: Portuguese (Native), English (Professional).

Education

  • Bachelor of Information Systems | University of Tocantins | 2016 - 2023
  • Technical Course in Programming and Computer Networks | Military Police College of Tocantins | 2013 - 2015
  • Work Authorization/Location Availability: Worldwide, United States of America (USA), Canada, Europe, United Kingdom (UK), Brazil