Hire senior DevOps / Platform Engineers from Latin America

Hire DevOps Engineers

Infra engineers who run AWS, GCP, or Azure at production scale. Terraform, Kubernetes, and CI/CD as second nature. For AI-specific infra, see MLOps. Onboarded in one week.

About the role

The DevOps Engineer role consists of owning the platform your software runs on — cloud infrastructure, CI/CD, reliability, cost. Good DevOps is invisible: deploys are boring, incidents are rare, and the AWS bill makes sense. Bad or absent DevOps is why your seniors spend Fridays fighting the pipeline instead of shipping.

Monthly rate

$4,500–$7,000/mo

All-in: contract, benefits, equipment, IP

Experience

10+ years typical

Location

Latin America

Argentina · Colombia · Mexico · Chile

Timezone

Full US overlap

Fluent English, onboarded in one week

Core stack

AWSGCPTerraformKubernetesDockerCI/CD (GitHub Actions, GitLab, ArgoCD)

AI tools, daily

Claude CodeCursor

Verticals seen

FintechSaaSE-commerceRegulated (HIPAA / PCI / SOC 2)

What they own — and what they don't

What they own

  • Design and run cloud infrastructure as code — Terraform on AWS, GCP, or Azure
  • Own CI/CD: fast, reliable pipelines from commit to production
  • Run Kubernetes and container platforms where they're warranted (and say when they're not)
  • Own reliability: monitoring, alerting, incident response, postmortems
  • Control cloud spend — right-sizing, reserved capacity, killing zombie resources

What they don't — and who does instead

  • Application code — they build the road, not the cars
  • ML model serving and GPU platforms — that's MLOps, a specialized sibling
  • Security as a full discipline — they harden infra, but audits and red teams are their own roles
  • Database administration at DBA depth — operational yes, query tuning is the app team's job

Who hires this role, and for what

  • Startups whose founders still hold the AWS root account. Infrastructure grew by accretion and now one wrong click is an outage. First DevOps hire turns it into a system.

  • Scale-ups with deploy fear. Releases are weekly, manual, and stressful. A senior DevOps makes deploys so boring they happen ten times a day.

  • Regulated companies facing compliance deadlines. SOC 2, HIPAA, PCI — auditors want infrastructure evidence that ad-hoc setups can't produce.

  1. 01

    Infrastructure-as-code adoption. From hand-built consoles to Terraform — reproducible, reviewable, recoverable.

  2. 02

    CI/CD overhaul. Pipelines that go from commit to production in minutes, with rollbacks nobody fears.

  3. 03

    Kubernetes done right (or avoided). Container orchestration where scale demands it — and simpler platforms where it doesn't.

  4. 04

    Cloud cost rescue. The bill audit that usually pays for the engineer within the quarter.

Work our engineers at this role have shipped

  • Multi-region AWS infrastructure for a Series C fintech ($2B annual volume)
  • GCP + Kubernetes migration for a healthcare SaaS with HIPAA requirements
  • GitLab CI/CD standardization for a 200-repo mono-org

Do you actually need a DevOps Engineer?

You do, if:

  • Deploys are manual, scary, or scheduled for late nights
  • One infrastructure person (or founder) is a single point of failure
  • The cloud bill grows faster than traffic and nobody can explain it
  • A compliance audit is coming and infrastructure evidence doesn't exist

You probably don't, if:

  • You're on a PaaS (Vercel, Heroku, Render) and it's working — don't hire for problems you've successfully outsourced
  • The pain is ML model serving — that's MLOps specifically
  • You need a one-time migration — scope it as a project first

Not sure which role fits? Tell us the problem instead of the title — we'll tell you what we'd actually staff, even if it's not this. If it is this: discovery call today, matched profiles in 48 hours, onboarded in a week.

Hire a Senior DevOps Engineer

Common questions

  • DevOps runs the platform your software runs on — infra, CI/CD, reliability. MLOps runs the platform your models run on — model registry, drift monitoring, evals, GPU orchestration. If your product is software with an ML feature, you probably need both.

Ready to talk?

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