Infrastructure / Site Reliability Engineer (SRE) (AI)

TL;DR

Infrastructure / Site Reliability Engineer (SRE) (Cloud/DevOps): Designing and maintaining scalable cloud infrastructure and automated deployment pipelines with an accent on Infrastructure as Code and system reliability. Focus on optimizing Kubernetes environments, building robust CI/CD workflows, and implementing comprehensive observability stacks to ensure production stability.

Location: Remote (Argentina, Brazil, Colombia, Georgia, Poland, Ukraine)

Company

AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence.

What you will do

• Design, provision, and maintain secure, scalable, and highly available cloud infrastructure on AWS, GCP, or Azure.
• Develop and maintain modular Infrastructure as Code (IaC) using Terraform or OpenTofu.
• Manage and optimize containerized environments using Docker and Kubernetes (EKS/GKE).
• Build and secure robust CI/CD pipelines via GitHub Actions, GitLab CI, or Jenkins to support zero-downtime deployments.
• Implement comprehensive observability stacks using Prometheus, Grafana, Datadog, or New Relic.
• Conduct chaos engineering, load testing, and root-cause analysis to ensure system resilience.

Requirements

• 3+ years of experience in an SRE, DevOps, or Cloud Infrastructure role.
• Deep production experience with at least one major cloud provider (AWS, GCP, or Azure).
• Strong proficiency with Terraform and hands-on experience managing production Kubernetes clusters.
• Solid understanding of Linux networking, internals, storage, and security fundamentals.
• Strong coding skills in Go or Python.
• Must be based in Argentina, Brazil, Colombia, Georgia, Poland, or Ukraine.

Nice to have

• Experience with GitOps workflows using ArgoCD or Flux.
• Knowledge of VPC architecture, DNS, load balancers (ALB/NLB), and CDNs.
• Familiarity with managing cloud-native databases (PostgreSQL, RDS) and caching layers (Redis, Memcached).

Culture & Benefits

• Opportunity to shape real-world AI-driven projects for clients ranging from startups to enterprises.
• Collaboration within a global team across different continents and cultures.
• Inclusive environment prioritizing continuous learning and innovation.
• Commitment to ethical AI standards.