Platform Engineer

Open English; Bogotá; In loco; COP 90.000.000 - 140.000.000; Tempo pieno

Descrizione del lavoro

Open English seeks a Platform Engineer to design and own the development experience for an AI-native engineering team. You will shape toolchains, CI/CD, and agentic capabilities, working directly with the CTO to enable a fast, secure, scalable pipeline in a global EdTech environment.

You will define frameworks, developer experience, and guardrails, ensuring production quality, memory of architectural decisions, and efficient collaboration across squads.

Competenze

• Platform Builder's track record in platform engineering or DevOps within lean, high-velocity teams.
• Active AI‑assisted development practitioner; built agentic workflows and multi‑agent systems.
• Strong hands‑on across AWS, infrastructure as code, CI/CD, and modern testing frameworks.
• Fluency in English; professional Spanish preferred.

Mansioni

• Own the Toolchain: select, configure, and evolve tools, environments, and model routing strategies for the team's daily workflow.
• Design the Golden Path: build scaffolding, shared configurations, and reusable skills to speed correct builds.
• CI/CD as a Product: architect agentic CI/CD pipelines and infrastructure as code on AWS with zero manual gates.
• Semantic Team Memory: design and implement shared memory to persist decisions and knowledge across sessions and engineers.
• Guardrails & Loops: build automated generation, self-review, and execution loops for the platform.
• Skills Arsenal: create and maintain the library of agent skills, evaluation suites, and multi‑agent prompts.
• E2E Testing Frameworks: own end‑to‑end testing architecture and production‑readiness checks.
• Instrument the Dev Process: measure developer experience and impact, such as lead time and token economics.
• Live on the Crest of the Wave: scan AI development frontier and pilot new models and frameworks.
• Multiply the Team: onboard engineers into the platform and evangelize new capabilities.
• Secure by Design: implement security with scoped permissions, secrets management, and audit trails.
• Protect Student Data: ensure privacy and compliance by design.
• Own Production Health: define SLOs, alerts, and incident response for the platform.
• Run It Like a Business: track AWS and AI spend efficiency.

Conoscenze

Platform engineering

DevOps

AI-assisted development

Multi-agent systems

AWS

Strumenti

Claude Code

Cursor

Terraform

CDK

CI/CD

Descrizione del lavoro

Open English has been a leader in English language teaching through virtual classes for over 15 years. We are proud to be a global and digital education (EdTech) the leading English-learning platform in over 30 markets, including Latin America, Brazil, the U.S. Hispanic market, Turkey, and Spain, among others. With over 3 million students enrolled to date, Open English is transforming the traditional language-learning model through its proprietary technology platform, offering unlimited, 24/7 access to live online classes with native-speaking instructors.

The company provides tailored solutions for individuals, businesses (Open English Business), and children (Open English Junior). It has also expanded its offering to include French, Italian, and Portuguese programs through Open Mundo. Backed by over $150 million in venture capital from top-tier firms such as Insight Partners and TCV, Open English continues to scale globally following its acquisitions of English Ninjas in Turkey and Enguru in India. The company is headquartered in Miami, with offices across Mexico City, Bogotá, Buenos Aires, Istanbul, Bangalore, and São Paulo.

We invite you to join us and be part of an innovative team dedicated to empowering our students. We are constantly seeking the best professionals in their fields to join our team. We offer the opportunity to work together and implement new ideas in a joyful and inspiring work environment.

Position Overview

Why is this role different? You aren't maintaining someone else's pipelines or filing infrastructure tickets. You get to design the entire development experience of an AI-native engineering team from absolute zero, with a mandate to innovate constantly and a CTO who expects you to stay ahead of the market. Nothing you ship goes unnoticed: every improvement multiplies the output of the whole team, and you will feel it within days, not quarters.

We aren't looking for a traditional DevOps engineer who keeps pipelines green and waits for infrastructure tickets. We are looking for a Platform Engineer: the architect of our development experience, someone who treats the engineering team as their product and builds the agentic machinery that lets a squad of ten ship like a company of fifty.

Working directly alongside the CTO, you will design and own the development architecture of our clean-sheet, agentic-first build. While our specialized product engineers own what gets built, you own how it gets built: the tools, frameworks, models, agent skills, testing harnesses, and CI/CD machinery that every engineer touches every single day. This role has no direct reports: you lead the platform, not people.

This is a role with a permanent innovation mandate. The AI development landscape reinvents itself every few weeks, and your job is to live on the crest of that wave: evaluating new models, agents, and frameworks as they appear, piloting the ones that matter, and retiring what no longer earns its place. If you want to build the factory that builds the product, this role is for you.

Main Responsibilities

1. Development Architecture & Developer Experience

• Own the Toolchain: Select, configure, and continuously evolve the tools, frameworks, agentic environments (Claude Code, Cursor, custom agents), and model routing strategies that define the team's daily workflow. Every choice is yours to make and yours to defend.
• Design the Golden Path: Build the paved road: project scaffolding, shared configurations, reusable skills, and templates that make the right way to build also the fastest way. Friction anywhere in the dev loop is your bug to fix.
• CI/CD as a Product: Architect agentic CI/CD pipelines, epistemic preview environments, and infrastructure as code on AWS that take a merged branch to production with zero manual gates and full confidence.

2. The Agentic Engine & Team Memory

• Semantic Team Memory: Design and implement the team's shared memory layer, so that architectural decisions, conventions, resolved bugs, and domain knowledge persist across sessions, agents, and engineers instead of evaporating after every chat.
• Guardrails & Loops: Build the automated generation, self-review, and execution loops that power our agentic-first build engine, wrapped in guardrails that let engineers move at full speed without breaking the platform.
• Skills Arsenal: Create and maintain the library of agent skills, evaluation suites, and multi-agent review prompts that encode how we build, and measure that they actually make the team faster.

3. Quality Automation & Observability

• E2E Testing Frameworks: Own the end-to-end testing architecture that builds quality into the pipeline itself. That includes automated regression suites, self-testing code and production-readiness checks, so engineers own quality and nobody waits for a separate QA phase.
• Instrument the Dev Process: Measure developer experience like a product: lead time, agent performance, token economics, flaky tests, and friction points. Use the data to decide what to improve next, and answer for the results.

4. Constant Innovation & Enablement

• Live on the Crest of the Wave: Continuously scan the frontier of AI-assisted development: new models, agent frameworks, eval tooling, and emerging patterns. Run structured pilots, adopt what works, and kill what does not.
• Multiply the Team: Onboard every engineer into the platform, document the golden path, and evangelize new capabilities so that every improvement you ship compounds across the whole squad within days.

5. Security, Reliability & Cost

• Secure by Design: Build security into the platform instead of adding it at the end. That means scoped permissions and sandboxing for every agent, secrets management, dependency and supply-chain scanning, and audit trails for agent-driven changes.
• Protect Student Data: Make sure the platform handles student data, including minors’ data where it applies, in line with privacy rules such as LGPD and GDPR. Compliance should be a default in the pipeline, not a checklist.
• Own Production Health: Define SLOs, alerting and incident response for the platform. Take part in an [on-call rotation], and make sure every incident leaves the system stronger.
• Run It Like a Business: Track and optimize AWS and AI-model spend. Every dollar of infrastructure and every token should earn its place.

What We're Looking For

• Platform Builder's Track Record: Proven experience in platform engineering, developer experience, or DevOps roles in lean, high-velocity teams, ideally where you built the development infrastructure from zero rather than inheriting it.
• Advanced AI Adaptation: An active, highly opinionated practitioner of AI-assisted development. You have built agentic workflows, custom skills, and multi-agent systems with tools like Claude Code and Cursor, not just used them out of the box.
• Deep Infrastructure Fundamentals: Strong hands‑on capability across AWS (VPC, ECS/EKS, Lambda, RDS), infrastructure as code (Terraform or CDK), CI/CD architecture, and modern testing frameworks.
• Product Mindset for Internal Tools: You treat engineers as your users: you watch how they work, find the friction, and ship improvements they feel immediately. You sweat the developer experience the way others sweat the UI.
• High Ownership: Exceptional self-direction and judgment. You are deeply uncomfortable with corporate bureaucracy and thrive when given a goal and a blank canvas.
• Languages: Fluency in English is required; professional proficiency in Spanish is strongly preferred.

Strong Advantage

• Hands‑on experience with LLM infrastructure: model routing, RAG and vector databases, semantic memory systems, or eval and observability frameworks for AI agents.
• Prior experience as a founding engineer or first platform hire at a startup.
• Contributions to developer tooling, open‑source agent frameworks, or internal AI platforms at a previous company.