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Made with coffee, code and curiosity, from Colombia ☕

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Jeyson Palacio

Jeyson Palacio

Senior Platform Engineer · Backend Architect

Senior Platform Engineer based in Bogotá. 10+ years in distributed backend, multitenant SaaS and cloud (AWS/GCP, Kubernetes), with Python, Ruby on Rails and React.

japalacio-08jeyson-anibal-palacio-palma

Resume

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Available for projects

PLATFORMENGINEER

Senior engineer and technical leader with 10+ years designing multitenant SaaS platforms, distributed systems and scalable backend architectures. I build the foundations and abstractions that scale teams and products.

Let's work togetherView projects
Years of experience
+10Years of experience
Projects delivered
+12Projects delivered
Clients & companies
+8Clients & companies
What your product needs

Services

From architecture to deployment: what your product gets in each area.

  1. 01

    Backend Architecture & APIs

    Your product ends up with a backend that survives growth: services with clear boundaries, documented APIs and a data model built for the queries that actually run.

    • REST and GraphQL APIs with versioned, documented contracts and contract tests.
    • Services in Python (Django, FastAPI), Node (NestJS, Express), Deno or Ruby on Rails, depending on what your team already runs.
    • PostgreSQL data model: schema, indexes, migrations and queries that do not degrade as the table grows.
    See what it includes
  2. 02

    Platforms & Distributed Systems

    When a product grows, the problem stops being a feature and becomes how the services talk to each other. That is where service boundaries, event delivery and flows that cannot be lost along the way come in.

    • Microservice design: where to cut, who owns which data and what contract sits between them.
    • Event-driven architecture on Kafka: topics, partitions, schemas and backward compatibility.
    • Durable workflows with Temporal for multi-step processes that must survive a restart.
    See what it includes
  3. 03

    Cloud, DevOps & IaC

    Infrastructure ends up described as code and deployment automated, so shipping to production is routine and anyone on the team can do it.

    • Infrastructure as code with Terraform or Pulumi, reviewable in a pull request.
    • CI/CD pipelines (GitHub Actions, Jenkins, Bitbucket) that build, test and deploy with no manual steps.
    • Containers and orchestration on Kubernetes, with resource limits, health checks and autoscaling.
    See what it includes
  4. 04

    AI Integration & Automation

    Models and agents go into the product you already have with the same discipline as any other service: a contract of your own, cost limits and a log of what they did.

    • Model API integration (Claude, GPT, Gemini) behind a contract of your own, so you can swap provider without touching the product.
    • MCP servers and clients to give a model controlled access to tools and data.
    • Agents that run multi-step tasks, orchestrated with Temporal when they need to be reliable.
    See what it includes
See all services
Career

Experience

10+ years building platforms, distributed systems and teams.

  1. Dec 2025 — PresentNowFreelance

    Randstad Digital · Torc

    Lead Engineer (Freelance) · Remote

    Leading technical architecture and delivery of scalable backend solutions for enterprise clients: Python microservices (Django/FastAPI), Rails services and CI/CD pipelines with IaC.

    PythonDjangoFastAPIRuby on RailsReactTerraformPulumiCI/CD
  2. Jun 2025 — Sep 2025Freelance

    FuseFinance

    Senior Backend Engineer (Freelance) · LATAM · Remote

    Built the backend architecture of a payments fintech: onboarding, KYC with banking integrations, payment queues (Celery/Redis) and an event-driven architecture with Kafka.

    PythonDjangoFastAPICeleryRedisKafkaReactTerraformKYC
  3. Jan 2024 — Jul 2026Full time

    Revelo · StyleSeat

    Senior Software Engineer · LATAM · Remote

    Through Revelo, dedicated engineer for StyleSeat: established and optimized booking features for beauty professionals, integrated third-party APIs (Braze, Segment) and added AI agents to automate their repetitive work.

    PythonRuby on RailsReactPostgreSQLBrazeSegmentAgentes de IA
  4. Feb 2021 — Jan 2024Full time

    BairesDev · Mastercard

    Senior Software Engineer · Remote

    Internal APIs and backend components for Mastercard’s multitenant payment infrastructure; low-latency system with Kafka and gRPC, AI fraud detection (MCP) and ClickHouse analytics.

    PythonKafkagRPCProtobufClickHouseApache AirflowReactMCP
See full experience
Recent work

Projects

A selection of things I have built.

  • Moveris

    Moveris

    Anti-fraud · AI liveness

    Digital identityNow

    Real-time fraud detection and human-liveness APIs; identification systems for AI-generated content and video.

    Read the case
  • StyleSeat

    StyleSeat

    Beauty & wellness marketplace · via Revelo

    Booking2026

    Booking features for beauty professionals: scheduling and availability, Braze and Segment integrations, and AI agents that automate repetitive work for professionals.

    Read the case
See all projects
Stack

Tools & Languages

Technologies I master, from frontend to infrastructure.

BackendFrontendDataMessagingCloud and DevOpsAI
See all tools
Let's talk

Contact

Have a project in mind? Reach out via the form or book a call.

Profiles & CV

japalacio-08jeyson-anibal-palacio-palma

Resume

Download CV

Book a call

Grab a time that works for you, or email me directly.

Book a callhey@jeyson.tech
From the blog

Articles

Notes on development, design and product.

See the whole blog
Seis barras escalonadas sobre una línea de tiempo de 0 a 620 milisegundos
Plain languageCloud and infrastructureAugust 13, 20264 min read

What happens in the half second between hitting Enter and seeing the page

You type an address, hit Enter and half a second later you are reading. Six things happen in that gap and almost none are what people picture. In plain language, with numbers from an ordinary page load.

Curva de espera frente a ocupación: plana hasta el 50 % y casi vertical cerca del 100 %
PerformanceArchitectureAugust 13, 20267 min read

The invisible queue: why a service slows down before it fills up

CPU reads 65 % and the p99 tripled. There is no bug, there is a queue. Why waiting grows all at once, where the queues in your stack hide, and what to do about them.