Senior Devops

About UsWe build and operate a fully-automated Speech Analytics SaaS platform running on Kubernetes across AWS and GCP.Our infrastructure processes ~160,000 hours of audio monthly with 99%+ uptime SLA, serving enterprise customers with mission-critical analytics needs.Our platform is built on modern, cloud-native technology: Kubernetes, Argo ecosystem, MongoDB, ElasticSearch, and 100% Terraform-driven Infrastructure as Code.We auto-scale from dozens to over 1,000 kubernetes nodes based on demand.Beyond our core SaaS product, we deliver managed solutions (Autopilot and Copilot platforms) and build AI-based services packaged as containerized, Terraform-ready modules for seamless integration into customer cloud environments (AWS, GCP, Azure).We're a team that values strong engineering practices, automation-first mindset, and operational excellence.About the RoleWe're looking for a Senior DevOps / Platform Engineer to help design, automate, and operate our cloud-native platform.You'll work across AWS and GCP, manage Kubernetes at scale, implement highly-automated CI/CD workflows, and collaborate with engineering teams to ensure reliable delivery of SaaS features and AI-driven products.What makes this role unique:Real ownership and autonomy - you'll be a key technical decision-makerWork directly with leadership on platform strategyHands-on with cutting-edge cloud-native and AI/ML workloadsOpportunity to lead a major AWS ? GCP migration to optimize costs and performanceThis role is ideal for someone who thrives in high-automation environments, enjoys solving complex platform challenges, and wants visible impact on products used by enterprise customers.Location: Fully remote (Spain-based)Key ResponsibilitiesInfrastructure & Cloud – Design, build, and maintain multi-cloud infrastructure on AWS and GCPOperate and optimize Kubernetes clusters (GKE, EKS) at scale (up to ~1K nodes)Lead infrastructure modernization and cloud migration initiativesImplement cost optimization strategies across cloud providersAutomation & CI/CD – Manage Argo Workflows and ArgoCD for GitOps-based deploymentsBuild and maintain end-to-end Infrastructure as Code with Terraform (modularized, reusable, multi-cloud)Develop internal automation tooling and scripts (Python, Bash, Go)Implement zero-downtime deployment strategiesPlatform Services – Deploy and manage production MongoDB, ElasticSearch, and other core servicesPackage and deploy workloads using Helm, Docker, and GitOps pipelinesEnsure 99%+ uptime SLA through robust monitoring and incident responseSupport delivery of AI containerized solutions ready for customer environmentsReliability & Observability – Build comprehensive observability across all platform componentsImplement security best practices and compliance requirementsDrive post-incident reviews and continuous improvementRequirementsMust Have5+ years as a DevOps, SRE, or Platform Engineer in production environmentsStrong hands-on Kubernetes experience (GKE and/or EKS) managing clusters at scaleExpert-level Terraform and Infrastructure as Code workflowsMulti-cloud experience with both AWS and GCPProven experience with CI/CD, GitOps, ArgoCD, Argo WorkflowsSolid Docker and Helm expertise for containerized deploymentsStrong scripting/programming skills in Python and BashExperience running production-grade, scalable, and secure cloud systemsComfortable with incident response and on-call responsibilitiesNice to HaveProgramming for tooling development (Python, bash, Go, ...)Experience with observability stacks (Prometheus, Grafana, Elastic, OpenTelemetry)Hands-on with AI/ML workloads in containerized environmentsMongoDB and ElasticSearch operations at scaleExperience with cost optimization strategies in cloud environmentsContributions to open-source DevOps/platform projectsAWS/GCP certificationsCompensation & BenefitsCompetitive salary packageFully remote work with flexible hours23 days of vacation + Spanish public holidaysGrowth & ImpactReal ownership - your decisions shape the platform's futureWork directly with leadership on technical strategyContinuous learning with modern cloud-native, DevOps, and AI toolingOpportunity to mentor and grow the team as we scaleVisible impact on products used by enterprise customersWork CultureEngineering-driven culture that values automation and best practicesAsync-first communication (we respect work-life balance)Blameless post-mortems and learning from incidentsRegular team knowledge-sharing sessions and open cooperationInterview ProcessInitial call (30 min)Technical interview (60 min)Final interviewTimeline: Typically 2-3 weeks from application to offerHow to ApplyApply here or send your CV and a brief note about what excites you about this role to ******#J-18808-Ljbffr