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About

Marc Canlas

Senior Software Engineer

I'm a full-stack engineer who has spent the last seven years taking SaaS products from concept to production. Most recently that has meant AI: designing agent workflows on OpenAI and Claude with real tool integrations, memory, and prompt frameworks that hold up under production traffic rather than in a demo.

The AI layer is only ever as good as what sits underneath it, so I own the whole path — Python and Node services exposing REST and GraphQL, authentication and authorisation, data pipelines across SQL and NoSQL, and the observability that makes failures legible instead of mysterious. On the other side I build the React and Next.js dashboards where that work becomes something a customer can act on.

I also work across content platforms — WordPress, Shopify and headless CMSs — modelling content so that the people who own it can ship without filing a ticket. Throughout, I've mentored engineers and set the testing and delivery standards that let teams move quickly without trading away reliability.

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Capabilities

Frontend

React and Next.js applications where the hard part is the data — analytics dashboards, AI-generated content review, and admin surfaces that stay quick as the payload grows.

  • React
  • Next.js
  • Vue.js
  • TypeScript
  • Tailwind CSS
  • Dashboards & data viz
  • Design systems
  • Accessibility

Backend

Python and Node services built to carry AI workloads: typed REST and GraphQL contracts, async processing and queues, hardened auth, and observability wired in from the first deploy.

  • Python
  • Node.js
  • REST APIs
  • GraphQL
  • PostgreSQL & NoSQL
  • Message queues
  • Docker & Kubernetes
  • OAuth2 / JWT
  • OpenTelemetry

CMS

Content and commerce platforms the owning team can actually run — WordPress and Shopify builds, headless architectures, and content models designed so routine changes never reach an engineer.

  • WordPress
  • Shopify
  • Sanity
  • Contentful
  • Payload
  • Headless architecture
  • Content modelling
  • Localisation

AI Training

LLM workflows that behave predictably in production: prompt frameworks, agent design with tools and memory, retrieval over vector stores, and the evaluation loop that keeps quality measurable.

  • OpenAI & Claude
  • Prompt engineering
  • Agent workflows
  • Memory management
  • RAG
  • Vector databases
  • LangChain / LangGraph
  • Evaluation & rubrics

Experience

  1. Jan 2024 — Apr 2026

    Senior Full Stack AI Engineer · Actual SEO Media

    Led end-to-end AI agent development for review-response workflows on OpenAI and Claude, integrating tools and memory for autonomous operation. Built the prompt-engineering framework that raised response reliability while cutting model cost by 18%, and kept integrations with Google Business Profile, Yelp and Facebook Reviews at 99.9% data-sync uptime.

    • Python
    • Node.js
    • React
    • Next.js
    • OpenAI
    • Claude
    • GraphQL

  2. Oct 2022 — Dec 2023

    Senior Software Engineer · BROCENT

    Built cloud-native Python and Node services exposing REST and GraphQL APIs for AI workloads and partner integrations. Dockerised CI/CD onto Kubernetes accelerated release cycles by 40%, and redesigned SQL/NoSQL data models doubled pipeline throughput. Mentored engineers and introduced the testing strategy.

    • Python
    • Node.js
    • Docker
    • Kubernetes
    • SQL
    • NoSQL

  3. Apr 2021 — Oct 2022

    Senior Full Stack Engineer · Scorch iProspect

    Architected backend microservices supporting AI workflows behind secure REST and GraphQL APIs, and built the React/Next.js dashboards that made AI metrics legible to clients — increasing engagement by 28%. Webhook-based review sync with retry logic held 99.8% data freshness.

    • Python
    • Node.js
    • React
    • Next.js
    • REST
    • GraphQL

  4. Jun 2019 — Feb 2021

    Software Engineer · Igen Technologies

    Full-stack SaaS development in Python and Node: scalable REST APIs over a service-oriented architecture, data pipelines across SQL and NoSQL, and authentication and authorisation across microservices. Observability and proactive incident response held 99.95% uptime.

    • Python
    • Node.js
    • SQL
    • NoSQL
    • Microservices

Education

  1. 2015 — 2019

    BSc Computer Science

    University of the Philippines