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Enfav LLC

About Enfav

Enfav LLC is an AI-focused software engineering company. We design and integrate AI-centered workflows that reduce repetitive manual steps and connect knowledge, people and existing applications.

Principles

  • Measured, not assumed

    Quality is defined up front and checked automatically — tests for software, critics and evaluators for AI.

  • Traceable decisions

    AI workflows keep a record of what was decided and why.

  • Built to be operated

    Observability, documentation and runbooks are part of the deliverable.

  • Plain dealing

    We say what we know, mark what we do not, and never present an unverified claim as fact.

Founder

Oscar Gonzalez

Founder & Chief Software Engineer

Oscar founded Enfav LLC in 2025 to bring production-grade AI automation and software engineering to commercial and public-sector teams, and personally leads its engineering work.

Oscar has more than ten years as a full-stack engineer, nine of them in lead and senior roles, building production software for entertainment, advertising technology and live-event ticketing platforms.

B.S. Computer Science, University of California San Diego, 2016

Newest first

Prior professional experience

The founder's own prior employment: evidence of technical experience, not Enfav LLC contract past performance.

  1. Madhive

    Senior Software Engineer (contract) · Jan 2026 – Jul 2026

    • Developed enterprise AdTech applications with TypeScript, Angular and Node.js, including reusable components and dynamic widgets for complex advertising workflows.
    • Drove AI-assisted Playwright end-to-end automation with Jest, Datadog and multimodal validation, cutting production bugs 50% and manual QA 60%.
    • Improved CI/CD regression workflows and automated quality checks, using Datadog and application logs to investigate defects and improve production reliability.

  2. Gala Games & Entertainment

    Lead Software Engineer · Jun 2024 – Jan 2026

    • Owned architecture, implementation, integrations and production delivery across consumer-facing entertainment applications.
    • Integrated the GCP Vision API, vector search and Sanity CMS to automate film content operations, thumbnail preparation, image selection and release metadata.
    • Architected Node.js and NestJS services on AWS and GCP with MongoDB, scaling media, collectibles and user-state workflows to 10,000+ concurrent users.

  3. Frequence

    Lead Software Engineer · Dec 2020 – Jun 2024

    • Helped lead Frequence's Angular framework, architecting extensible widgets and configurable UI workflows for AdTech automation.
    • Automated AI-assisted browser regression across high-variation customer paths, improving release confidence for production-critical workflows.
    • Provided technical direction for 30+ engineers and QA specialists across architecture, testing strategy, design systems and code-review standards.

  4. TicketSocket & IceCreamSocial

    Lead Full Stack Developer · Jun 2017 – Dec 2020

    • Migrated AngularJS to React and TypeScript, improving architecture, testability and design-system reuse.
    • Re-architected AWS ticketing services, scaling from 350 to 10,000+ concurrent users.
    • Optimized PostgreSQL data flows with indexing, stored procedures, triggers, webhooks and transactional event processing.
    • Raised test coverage from near zero to 70% across a 90,000+ line codebase and created Redocly and Swagger API documentation for partner onboarding.

  5. Visa

    Full Stack Engineer · Jun 2016 – May 2017

    • Built Angular and D3.js risk dashboards with data-science teams to surface infrastructure exposure across Visa's network, reducing incidents 30%+.
    • Developed a real-time Angular and Node.js vendor portal that cut third-party tool approval cycles 80%+.

Not client work

Founder-developed AI systems

Built by the founder since 2025 and continued at Enfav; not client work.

  1. Multi-agent workflow engine

    Goal-to-DAG task planning, tool calling and MCP, strict schemas, language-model critics and evaluations, contextual memory and retrieval.

  2. RAG and search pipelines

    Vector embeddings, semantic and hybrid retrieval, reranking and contextual grounding for searchable document and data workflows.

  3. AI architecture evaluator

    Graph-based system-design components with critic and evaluation pipelines for iterative architecture review.

  4. Agentic browser automation

    Playwright-based multi-step browser sessions, UI validation and tool-integrated test workflows.

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