Senior Platform Engineer Role (Devops)

Job description

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Platform Engineer Role (DevOps) based in Mexico.** We are looking for an experienced Senior Platform Engineer to help build a modern platform engineering function from the ground up. In this high-impact individual contributor role, you will lead cloud modernization across AWS and Azure, establish robust site reliability engineering (SRE) and observability practices, and develop an Internal Developer Platform that empowers engineering teams to deliver software faster and more securely. You will design scalable infrastructure, automate cloud operations, and create standardized workflows that make self-service development possible. Working closely with engineering leadership and cross-functional teams, you will embed security, reliability, and cost efficiency into every layer of the platform. This is an opportunity to shape foundational architecture, influence engineering standards, and drive meaningful improvements across the software delivery lifecycle. ### Accountabilities - **Cloud Modernization and Infrastructure as Code** - Re-architect and codify existing AWS and Azure infrastructure using OpenTofu/Terraform and Ansible, establishing reusable modules, remote state management, and GitOps-based infrastructure pipelines. - Assess cloud environments against AWS and Azure Well-Architected Frameworks, prioritize remediation, and improve networking, identity and access management, landing zones, account structures, and cost governance. - Implement policy-as-code using tools such as OPA, Conftest, AWS Service Control Policies, and Azure Policy to enforce security, compliance, and resource-tagging standards. - Build and maintain reusable infrastructure modules for compute, Kubernetes, networking, storage, databases, and identity services. - Establish FinOps practices, including cost allocation, tagging standards, dashboards, resource rightsizing, and reserved capacity planning. - **Site Reliability Engineering and Observability** - Design and maintain an end-to-end observability stack covering metrics, logs, traces, and dashboards using technologies such as Prometheus, Grafana, Loki, Tempo, Datadog, and OpenTelemetry. - Define service-level indicators (SLIs) and objectives (SLOs) for shared platform services and critical applications, supported by error budgets and burn-rate alerting. - Establish SRE practices, including incident runbooks, post-incident reviews, and chaos engineering exercises. - Collaborate with engineering teams to instrument services, develop actionable alerts, and build operational dashboards that improve service reliability. - Develop compute and storage capacity-planning models to support informed scaling and infrastructure investment decisions. - **Internal Developer Platform and Automation** - Deploy and operate a centralized developer portal, such as Backstage or an equivalent solution, providing a service catalog, scaffolding templates, documentation, runbooks, API references, and on-call ownership information. - Create and maintain standardized development workflows for service creation, Kubernetes deployment, database provisioning, secrets management, and CI/CD configuration. - Own the CI/CD platform layer, including reusable GitHub Actions or GitLab CI workflows, container build and scanning pipelines, and secure environment promotion processes. - Manage Kubernetes platform operations across EKS and/or AKS, including cluster lifecycle, Helm standards, admission controllers, role-based access control (RBAC), network policies, and service mesh technologies. - Build self-service provisioning capabilities that enable developers to deploy approved resources without manual ticket-based processes. - Monitor platform adoption, gather developer feedback, and continuously improve workflows based on real-world needs. - **Security, Collaboration, and Technical Leadership** - Partner with engineering teams to plan and execute workload migrations, providing hands-on technical support throughout the transition. - Integrate security controls into platform workflows, including infrastructure scanning, secrets management, access controls, and container image hardening. - Produce clear technical documentation, architecture decision records, operational runbooks, and implementation guidance. - Mentor junior platform engineers, contribute to architecture reviews, and support build-versus-buy decisions alongside engineering leadership. ### Requirements: - At least 5 years of experience in platform engineering, infrastructure engineering, or DevOps, with direct production ownership of AWS and/or Azure environments. - Strong proficiency in OpenTofu/Terraform, including reusable module development, state management, workspace strategies, remote backends, and CI/CD integration. Experience with Terramate is an advantage. - Extensive Kubernetes operations experience, including EKS and/or AKS cluster management, Helm, admission controllers, RBAC, network policies, and autoscaling. - Hands-on experience with at least two observability technologies, such as Prometheus, Grafana, Loki, Tempo, Datadog, or OpenTelemetry, including SLI/SLO design and alert engineering. - Experience building and maintaining CI/CD platforms, authoring GitHub Actions pipelines, designing reusable workflows, and managing container build and security scanning processes. - Familiarity with GitOps tools such as Argo CD or Flux for Kubernetes continuous delivery. Knowledge of canary and blue-green deployment strategies is a plus. - Experience with Internal Developer Platforms, Backstage or similar developer portals, service catalogs, scaffolding templates, or self-service infrastructure provisioning. - A security-first mindset, with practical knowledge of policy-as-code, infrastructure security scanning, secrets management, container hardening, and shift-left security practices. - Strong communication and technical documentation skills, with the ability to explain architecture decisions to engineers, stakeholders, and leadership. - The ability to work independently, collaborate across teams, and take ownership of complex technical initiatives from design through production. **Additional qualifications that are an advantage:** - Experience with chaos engineering, error budget management, incident command, and capacity planning. - Knowledge of Istio or Linkerd, including mutual TLS (mTLS), traffic management, and observability integration. - Familiarity with FinOps tools such as Kubecost or CloudHealth and experience with reserved capacity planning. - Understanding of AI/ML infrastructure, including LLM API integration or model-serving workloads. - Relevant certifications, such as AWS Solutions Architect, Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), Azure Administrator, Azure Solutions Architect, or HashiCorp Terraform Associate. - Proficiency in Python or Go for developing platform automation, internal tools, and command-line interfaces. ### Benefits: - **Foundational technical ownership:** Help build a platform engineering function from the ground up and influence its architecture, standards, and long-term direction. - **Broad technical impact:** Work across cloud infrastructure, Kubernetes, automation, observability, security, and developer experience. - **Engineering autonomy:** Take ownership of significant technical initiatives and translate architectural strategy into production-ready solutions. - **Cross-functional collaboration:** Partner with engineering teams and leadership to improve reliability, developer productivity, and software delivery. - **Professional development:** Expand your expertise in modern cloud technologies, SRE practices, infrastructure automation, and platform engineering. - **Technical leadership opportunities:** Mentor other engineers, contribute to architectural decisions, and establish engineering best practices. - **Modern technology environment:** Work with AWS, Azure, Kubernetes, GitOps, Infrastructure as Code, and emerging AI/ML infrastructure requirements.