# Platform Engineer (AI Automation)

**Company**: EarnIn
**Location**: Mexico City
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/earnin/jobs/8346674?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_bf0c0ed7-7ab

## Description

## Job Summary

We're seeking a Platform Engineer (I3) who is an AI-native builder, someone who doesn't just use AI tools but designs and deploys AI agents to eliminate toil, accelerate developer workflows, and multiply what a lean team can deliver.

## Responsibilities

- AI-Agent Development: Design, build, and iterate on AI agents that automate platform operations, from service and infra bootstrap, intelligent incident diagnosis, automated runbook execution, to self-healing infrastructure and PR-review bots. Own the agent lifecycle: prompt engineering, tool/function-call orchestration, evaluation, and production monitoring.

- Workflow Automation with AI: Identify and eliminate repetitive human-in-the-loop workflows across CI/CD, environment management, access provisioning, and change management.

- Developer Self-Service: Evolve our developer control plane (Cortex) into an AI-augmented self-service platform where engineers interact with intelligent assistants, not just dashboards, to scaffold services, debug deployments, query platform health, and resolve issues without filing tickets.

- Delivery & GitOps: Implement and maintain GitOps-based continuous delivery with Argo CD, integrating AI into CI pipelines for intelligent test selection, automated config validation, and deployment risk scoring.

- Kubernetes Infrastructure: Operate and evolve our Kubernetes platform on AWS EKS, focusing on environment hygiene, security, and cost efficiency, leveraging AI for anomaly detection, capacity recommendations, and automated remediation.

- Observability & Operational Excellence: Strengthen reliability by monitoring SLOs/error budgets and utilizing Datadog for metrics, traces, and logs, building AI-driven alerting and root-cause-analysis agents that reduce mean-time-to-resolution.

- Service Standardization: Maintain service scaffolds and templates that encode standards for testing and telemetry, using AI to auto-generate and validate configurations against platform baselines.

## Requirements

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- 3+ years in platform, infrastructure, or backend engineering with deep knowledge of Kubernetes (EKS) and cloud-native architectures on AWS.

- Demonstrated experience building AI agents or agentic workflows, not just using Copilot or ChatGPT, but designing multi-step AI systems that autonomously perform operational tasks.

- A track record of automating repetitive workflows with AI.

- Experience in GitOps (ArgoCD) and CI (GitHub Actions) for multi-service systems.

- Strong coding skills in Go and/or Python, treating infrastructure as software.

- Excellent communication skills; able to clearly convey technical problems and advocate for both team and customer needs.

- Experience with LLM orchestration frameworks and prompt engineering for production systems.

## Benefits

EarnIn offers excellent employee benefits, including healthcare, internet and cell phone reimbursement, a learning and development stipend, and potential opportunities to travel to our headquarters in Mountain View.

## Skills

### Required
- Kubernetes
- AWS EKS
- GitOps
- Argo CD
- CI/CD
- GitHub Actions
- AI-agent development
- Python
- Go
- Datadog

### Nice to have
- LLM orchestration frameworks
- LangChain
- LlamaIndex
- CrewAI

---

Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/earnin/jobs/8346674?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)