AI that holds up in production.

I'm Kevin Bayter, an AI Engineer and Tech Lead in Bogotá. Founder of Skyfold Labs and Tech Lead of the payments layer at WOM Colombia.

Available · fully remote Bogotá

A Transformer, piece by piece Assembling the architecture…
The architecture behind the AI models I work with, assembled step by step: tokens, embeddings, attention, stacked layers and the prediction of the next token.
Based in
Bogotá, Colombia · remote
Today
Tech Lead at WOM Colombia
Before
Almost four years at Mercado Libre

I modernize critical payments and high-traffic platforms, and design AI agents with deterministic guardrails, where a mistake is not an option.

  • Go
  • TypeScript
  • Kubernetes
  • AWS / EKS
  • Redis
  • Terraform
  • Next.js
  • PostgreSQL
  • APISIX
  • Playwright
  • Grafana
  • AI agents

Founder of Skyfold Labs

An applied artificial intelligence lab.

We research and build AI systems that run on device and in the cloud. The lab also publishes its own mobile apps; the first one is Lunzi. Here is how it comes together, piece by piece.

  1. Launch pad

    Security and privacy

    Everything rests on this: privacy and security by design, not as an afterthought.

  2. Engines

    AI models

    The lab's thrust: models running on device and in the cloud.

  3. First stage

    Research

    We explore what AI can solve today in everyday problems.

  4. Second stage

    Engineering

    We turn those models into products that hold up under real use.

  5. Payload

    Mobile apps

    What reaches people: the apps the lab publishes. The first one is Lunzi.

  6. Fairing

    Design

    Assistants that understand context and feel natural to use.

  7. Countdown

    Ready for launch

    More AI apps for everyday life are on the way.

A lab powered by AI Scroll to assemble it
lunzi

Lunzi, the lab's first app

An AI trip planner for Android. Tell it where you want to go and it builds your trip day by day with real places, tells you what is missing and keeps you company while you travel.

Meet Lunzi

Closed beta on Google Play · Made in Colombia, in Spanish and English

Illustrative screens, based on the app.

Selected work

Systems in production, with their architecture and what I value most in each.

Tech Lead · WOM Colombia

Deployment platform

The internal platform the whole team ships with: from a push to production with ephemeral environments, managed secrets, a chat bot and an audit trail for every step.

  • Kubernetes
  • AWS / EKS
  • Terraform
  • GitLab CI
  • Redis
Team chat#deploys
You
/deploy api v1.2
Deploy bot
Signed image in the registrydone
Ephemeral namespace with its own URLdone
Environment smoke testspassed
Production · 2 replicasdeployed

From a push to production

  1. A push or a commandA deploy starts with a git push, a chat command or the UI. Everything enters through a central API that checks role-based permissions.
  2. The API queues the workBuilds, rollouts and smoke tests run on async workers coordinated through Redis queues. The UI never blocks waiting.
  3. Quality in parallelLint, unit, e2e and coverage run at once with per-branch caching. If they pass, an unprivileged OCI image is built and signed in the private registry.
  4. Ephemeral environmentEach feature deploys to an isolated namespace with its own URL. Secrets are injected encrypted at runtime and smoke tests run against that environment.
  5. Production on two targetsThe same flow promotes to on-premise Kubernetes and to AWS EKS, with one-click rollback to the previous version.
  6. Everything is auditedEvery step is written to an immutable log, metrics reach Prometheus and Grafana, and the bot replies in the chat with the result.

Highlights

  • 100% of the development team ships daily with the platform.
  • One ephemeral environment per feature, with its own URL, created and destroyed automatically.
  • Nothing reaches production without passing the ephemeral environment smoke tests.
  • One-click rollback to the previous version, with full history.
  • Zero secrets in repositories: encrypted runtime injection, masked in every log.
  • Deploy from the chat, without opening consoles or dashboards, with role-based permissions.
  • One flow, two targets: on-premise and cloud.

Infrastructure · WOM Colombia

On-premise cluster

I built the team's on-premise platform from scratch: a declaratively managed Kubernetes cluster with an API gateway, automatic TLS, highly available data and full observability.

  • Kubernetes
  • APISIX
  • cert-manager
  • PostgreSQL
  • Prometheus
Cluster servicesonline
APISIXgateway · auth and rate limiting
cert-managerautomatic TLS
Postgreshigh availability
Rediscache and queues
Registrysigned images
Prometheus · Grafanametrics and alerts

The cluster, layer by layer

  1. A single entry pointAll traffic enters through the API gateway, which authenticates, rate-limits and terminates TLS with certificates issued by cert-manager.
  2. Isolated servicesEach service runs in its own pods with signed images from the private registry. Each feature gets its own ephemeral namespace.
  3. Highly available dataPostgres run by an operator in high availability, and Redis for cache and queues.
  4. Full observabilityPrometheus collects metrics from every service, Grafana shows them in dashboards and alerts fire before a user notices.

Highlights

  • An on-premise Kubernetes cluster built from scratch and scaled.
  • Declarative end to end: the infrastructure lives as code.
  • Automatic TLS on every service in the cluster.
  • Highly available Postgres with an operator, plus Redis for cache and queues.
  • Metrics, dashboards and alerts for every service.

Creator · open source

TuRenta AI

Automates Colombia's income tax return (form 210). AI agents extract the data from tax reports and certificates, interview you, and a 100% deterministic tax engine computes the tax.

  • TypeScript
  • Next.js
  • PostgreSQL
  • Redis
  • Playwright
turenta.tax
Form 210Sample data
Employment income$ 96.400.000read by AI
Tax withheld$ 4.180.000read by AI
Dependents1confirmed
25% exempt income$ 15.900.000computed
Balance due$ 1.732.000

AI reads, code computes

  1. DownloadPlaywright signs in to the tax authority and downloads reports, certificates and past returns. The work runs on async workers with Redis.
  2. ExtractAgents read every document and extract structured data with a double read of each value. It is the only stage that uses AI.
  3. You confirmA guided interview shows you every extracted value, and nothing is used until you confirm it.
  4. ComputeA 100% deterministic engine computes form 210 with rules that cite the law. A golden test reproduces a real return line by line.
  5. An architecture that defends itselfHexagonal boundaries enforced by ESLint and architecture tests, in a Turborepo monorepo with Docker images and GitHub Actions.

Highlights

  • In a domain where a hallucination is a legal problem, AI never does the math.
  • A golden test that reproduces a real tax return line by line.
  • Hexagonal architecture with boundaries enforced by ESLint and architecture tests.
  • Double read and human confirmation of every value before it is used.
  • Async workers with Redis for queues, rate limiting and sessions.

Full-stack

Feedback360

A complete professional feedback platform: teams with visibility levels, real-time notifications, Google and OTP login, goal management and an admin dashboard.

  • React
  • Node.js
  • Express
  • MongoDB
New feedbackProduct team
PublicPrivateCompany
Great job running the sprint retro.Visible to your organization
Quarterly goalSample progress

As Tech Lead at WOM

I lead the modernization of the payments layer and its integrations with the core business services. This is what I value most in the role.

A platform the whole team uses

I built the internal deployment platform: it orchestrates on-premise Kubernetes and AWS/EKS, infrastructure as code, secrets and change traceability across environments.

Standard delivery across teams

End-to-end auditable rollouts for several teams, with less friction and fewer manual errors in production.

AI inside the engineering cycle

I drive its day-to-day adoption: assisted code review, alert analysis and automation of operational tasks.

Payments that can't go down

Evolving the BSS and payments ecosystem with a focus on resilience, scalability and continuity, with Redis for caching and idempotency in transactional flows.

How I build: from spec to deploy

Spec-driven development with AI agents working in parallel. Every feature starts as an executable spec, and nothing is merged without tests, architecture lint and human review.

  • The spec first: goal and acceptance criteria before any code.
  • Agents in parallel, each one with a part of the spec.
  • E2E with Playwright against the real production build, before every merge.
  • Pipelines with parallel quality and per-branch caching: feedback in minutes.

Proven in production

years building production systems
5+
of the team ships daily with my platform
100%
targets with the same flow: on-premise and cloud
2
secrets in repositories, with encrypted runtime injection
0

Path

From IT support in Cartagena to leading payments and founding an AI lab.

Experience

  1. Now

    Founder

    Skyfold Labs S.A.S.

    An applied AI lab that also publishes mobile apps. The first one: Lunzi.

  2. Nov 2025 — now

    Software Engineer Specialist · Tech Lead

    WOM Colombia · Bogotá

    I lead the modernization of the payments layer and its integrations with APISIX, secrets, observability and Redis for idempotency in transactional flows.

  3. Jan 2022 — Sep 2025

    Software Engineer

    Mercado Libre · Bogotá

    Backend and front end with Go, Node.js, TypeScript and Next.js on 24/7 high-traffic services, with observability and AI automations.

  4. 2017

    IT Support Specialist

    Facture S.A.S. · Cartagena

    Software and hardware support, and proactive monitoring to reduce downtime.

Education

  1. 2025

    Cloud Computing, AWS and Azure

    Universidad de los Andes

  2. 2022 — 2026

    Systems Engineering

    Fundación Universitaria del Areandina

  3. 2021 — 2022

    Fullstack Developer Bootcamp

    Henry · 800+ hours

Let's talk

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kevin@bayterx.com