Senior Platform Engineer Role (Devops)
- Compensation
- Not disclosed
- Location
- Mexico, Mexico
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Devops
- Posted
Skills
Must have
- ● 5+ years in platform, infrastructure, or DevOps engineering with direct production ownership on AWS and/or Azure
- ● IaC: Deep OpenTofu/Terraform proficiency: module authoring, state management, workspace strategy, remote backends, and CI/CD integration; Terramate a plus
- ● Kubernetes: Strong Kubernetes operations: EKS and/or AKS cluster lifecycle, Helm, admission controllers, RBAC, network policies, and autoscaling
- ● Observability & SRE: Hands-on observability experience with two or more of: Prometheus, Grafana, Loki, Tempo, Datadog, or OpenTelemetry — including SLI/SLO definition and alert engineering
- ● CI/CD: CI/CD platform experience: GitHub Actions pipeline authoring, reusable workflow design, and container build/scan pipeline ownership
- ● GitOps: GitOps: ArgoCD or Flux for Kubernetes continuous delivery; progressive delivery patterns (canary, blue-green) a strong plus
- ● IDP: IDP experience: Backstage or equivalent developer portal, GitHub, scaffolding templates, service catalog design, or self-service provisioning tooling
- ● Security: Security-first mindset: policy-as-code, IaC scanning, secrets management, container hardening, and shift- left security practices
- ● Strong communication and documentation skills; comfortable presenting architecture decisions to engineering peers and leadership
Nice to have
- ● SRE background: chaos engineering (AWS FIS, Chaos Monkey), error budget management, incident command, and capacity planning
- ● Service mesh depth: Istio or Linkerd — mTLS, traffic management, and observability integration
- ● FinOps tooling (Kubecost, CloudHealth) and reserved capacity planning experience
- ● Familiarity with AI/ML infrastructure basics: LLM API integration or model serving, as the platform will need to support these workloads
- ● Certifications: AWS Solutions Architect Associate/Professional, CKA/CKAD, Azure Administrator/Solutions Architect, HashiCorp Terraform Associate
- ● Python or Go for platform tooling and CLI development
Full description
About the role:
As a Senior Platform Engineer, become a part of a cross-functional development team engineering experiences of tomorrow. Our client is building a platform engineering function from the ground up and this role is at the center of it. As a Senior Platform Engineer you will be a founding team member with a clear, three-part mission: fully rearchitect and codify our cloud estate on AWS and Azure, stand up a world-class SRE and observability practice, and build an Internal Developer Platform with golden paths that make shipping software fast, safe, and self-service. This is a high-ownership individual contributor role. You will work directly with the Platform Engineering Manager to translate strategy into production infrastructure, drive adoption across engineering teams, and set the technical bar for how the platform is built and operated.
Responsibilities:
● Cloud Modernization — Rearchitect & Codify:
○ Migrate all existing AWS and Azure infrastructure to OpenTofu/Terraform and Ansible; establish module standards, remote state, and GitOps-based plan/apply pipelines — no unmanaged resources
○ Audit the cloud estate against the AWS and Azure Well-Architected Frameworks; produce a remediation backlog and drive it to completion across networking, IAM, landing zones, account structure, and cost governance
○ Implement policy-as-code (OPA/Conftest, AWS SCPs, Azure Policy) to enforce security, tagging, and compliance guardrails at the platform layer — governance embedded, not bolted on
○ Build and maintain reusable Terraform modules for compute (EKS, AKS, EC2), networking, storage, databases, and identity as shared building blocks for all engineering teams
○ Define FinOps standards: tagging taxonomy, cost allocation dashboards, rightsizing recommendations, and reserved capacity planning across both clouds
● SRE & Observability:
○ Design and implement the full observability stack: metrics (Prometheus/Datadog), logs (Loki/OpenSearch), traces (Tempo/Datadog APM), and dashboards (Grafana) — instrumented end-to-end via OpenTelemetry
○ Define SLIs and SLOs for all platform shared services and critical applications; build error budget dashboards and burn-rate alerting — alert on symptoms, not raw metrics
○ Establish the SRE practice from scratch: incident runbooks, post-incident review templates, and at least one chaos engineering exercise (AWS FIS or equivalent)
○ Partner with engineering teams to instrument their services, define meaningful alerts, and build operational dashboards — reliability is a shared responsibility, not a platform team tax
○ Build capacity planning models for compute and storage so engineering leadership can make data-driven scaling decisions