About Us
We 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 Role
We'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-maker.
Work directly with leadership on platform strategy.
Hands‑on with cutting‑edge cloud‑native and AI/ML workloads.
Opportunity to lead a major AWS / GCP migration to optimize costs and performance.
This role is ideal for someone who thrives in high‑automation environments, enjoys solving complex platform challenges, and wants a visible impact on products used by enterprise customers.
Location
Fully remote (Spain‑based)
Key Responsibilities
* Design, build, and maintain multi‑cloud infrastructure on AWS and GCP.
* Operate and optimize Kubernetes clusters (GKE, EKS) at scale (up to ~1K nodes).
* Lead infrastructure modernization and cloud migration initiatives.
* Implement cost optimization strategies across cloud providers.
* Manage Argo Workflows and ArgoCD for GitOps‑based deployments.
* Build 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 strategies.
* Deploy and manage production MongoDB, ElasticSearch, and other core services.
* Package and deploy workloads using Helm, Docker, and GitOps pipelines.
* Ensure 99%+ uptime SLA through robust monitoring and incident response.
* Support delivery of AI containerized solutions ready for customer environments.
* Build comprehensive observability across all platform components.
* Implement security best practices and compliance requirements.
* Drive post‑incident reviews and continuous improvement.
Requirements
* Must Have
* 5+ years as a DevOps, SRE, or Platform Engineer in production environments.
* Strong hands‑on Kubernetes experience (GKE and/or EKS) managing clusters at scale.
* Expert‑level Terraform and Infrastructure as Code workflows.
* Multi‑cloud experience with both AWS and GCP.
* Proven experience with CI/CD, GitOps, ArgoCD, Argo Workflows.
* Solid Docker and Helm expertise for containerized deployments.
* Strong scripting/programming skills in Python and Bash.
* Experience running production‑grade, scalable, and secure cloud systems.
* Comfortable with incident response and on‑call responsibilities.
* Nice to Have
* Programming for tooling development (Python, bash, Go, ...).
* Experience with observability stacks (Prometheus, Grafana, Elastic, OpenTelemetry).
* Hands‑on with AI/ML workloads in containerized environments.
* MongoDB and ElasticSearch operations at scale.
* Experience with cost optimization strategies in cloud environments.
* Contributions to open‑source DevOps/platform projects.
* AWS/GCP certifications.
Compensation & Benefits
* Competitive salary package.
* Fully remote work with flexible hours.
* 23 days of vacation + Spanish public holidays.
* Growth & Impact: Real ownership – your decisions shape the platform's future.
* Work directly with leadership on technical strategy.
* Continuous learning with modern cloud‑native, DevOps, and AI tooling.
* Opportunity to mentor and grow the team as we scale.
* Visible impact on products used by enterprise customers.
* Engineering‑driven culture that values automation and best practices.
* Async‑first communication (we respect work‑life balance).
* Blameless post‑mortems and learning from incidents.
* Regular team knowledge‑sharing sessions and open cooperation.
Interview Process
* Initial call (30 min).
* Technical interview (60 min).
* Final interview.
Timeline
Typically 2–3 weeks from application to offer.
How to Apply
Apply here or send your CV and a brief note about what excites you about this role to ******.
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