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
1. must have
2. 5+ years as a devops, sre, or platform engineer in production environments.
3. strong hands‑on kubernetes experience (gke and/or eks) managing clusters at scale.
4. expert‑level terraform and infrastructure as code workflows.
5. multi‑cloud experience with both aws and gcp.
6. proven experience with ci/cd, gitops, argocd, argo workflows.
7. solid docker and helm expertise for containerized deployments.
8. strong scripting/programming skills in python and bash.
9. experience running production‑grade, scalable, and secure cloud systems.
10. comfortable with incident response and on‑call responsibilities.
11. 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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