!Please note that this job requires to work within european hours!
Satellite and drone imagery access is on the rise, and traditional image processing methods are struggling to keep up. We’ve never had more data, and yet it’s never been harder to gain meaningful insights.
Our scalable AI platform enables custom model training on global features, providing real-time, on-demand geospatial insights with impressive speed and accuracy. The application turns months of manual work into mere minutes, and with much better results. We work with customers from various domains, from intelligence and defence, local and federal governments, insurance industry, to small and large enterprises, which requires us to have a lot of flexibility on how we deploy and maintain our services.
We kicked off in 2020 and have secured $35 million in series A funding from a lineup of top US and European investors, among which Microsoft M12, Point72 Ventures, Maxar, In-Q-Tel, SAFRAN, and ISAI/Capgemini.
We're searching for a Platform Engineer to join our Deployment team. You'll build and operate the infrastructure that powers our AI platform across radically different environments: AWS for our SaaS offering, single-tenant cloud deployments for enterprise customers, K3S clusters on customer hardware, and edge deployments running on a single laptop in the field. You'll also shape the developer experience for our engineering teams, making it easy to build, test, and ship reliable software.
What you'll do
Build and operate Kubernetes clusters across AWS, Azure, GCP and bare-metal K3S deploymentsOwn infrastructure as code using Terraform, evolving our multi-environment architectureDesign and improve CI/CD pipelines to accelerate the path from code to productionEnhance observability across the stack with Prometheus, Grafana, and the ELK stackMaintain security standards required for defence and government customersOptimize cloud costs while ensuring performance and reliabilityTravel to customer sites to support on-premises deployments and troubleshoot production issuesEnsure testing and staging environments are reproducible and consistent with production
Your profile
Experience with Docker, Kubernetes, and Terraform in production environmentsStrong Linux system administration skills with the ability to debug production issuesSolid understanding of networking, security, and infrastructure fundamentalsExperience with CI/CD pipelines and deployment automationGood communicator who enjoys working in a team and can context-switch across prioritiesComfortable traveling to customer sites for on-premises deploymentsScripting proficiency in Python and Bash
Ideally:
Experience with multi-environment or multi-tenant deployment architecturesBackground in regulated environments (government, defence)Familiarity with GPU infrastructure and ML workload schedulingExperience with K3S or lightweight Kubernetes distributions for edge deploymentsKnowledge of container security scanning and hardening practices
Why join us
Unique deployment challenges: Few teams operate across SaaS, enterprise cloud, on-prem servers, and edge laptops—you'll solve problems most engineers never encounterStrategic impact: The Deployment team is central to our defense expansion, directly enabling new customer segments and contract opportunitiesCustomer-facing work: Travel to customer sites and see your infrastructure running in real operational environmentsGrowth trajectory: Join ahead of our Series B as we scale the team and expand into new marketsStrong technical culture: Work alongside platform, ML, and GIS engineers solving novel infrastructure challengesHealthy work-life balance with flexible working arrangementsCompetitive compensation with personalized benefits including learning opportunities, mental well-being programs, and healthcare
Tech Stack
Linux, Docker, Kubernetes (EKS, K3S)AWS, Azure, GCPTerraformAzure DevOps, ArgoCD, HelmPrometheus, GrafanaElasticsearch, KibanaRedis, PostgreSQLPython, Bash
