Platform Engineer - Deployment Team

!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 deployments
• Own infrastructure as code using Terraform, evolving our multi-environment architecture
• Design and improve CI/CD pipelines to accelerate the path from code to production
• Enhance observability across the stack with Prometheus, Grafana, and the ELK stack
• Maintain security standards required for defence and government customers
• Optimize cloud costs while ensuring performance and reliability
• Travel to customer sites to support on-premises deployments and troubleshoot production issues
• Ensure testing and staging environments are reproducible and consistent with production

Your profile

• Experience with Docker, Kubernetes, and Terraform in production environments
• Strong Linux system administration skills with the ability to debug production issues
• Solid understanding of networking, security, and infrastructure fundamentals
• Experience with CI/CD pipelines and deployment automation
• Good communicator who enjoys working in a team and can context-switch across priorities
• Comfortable traveling to customer sites for on-premises deployments
• Scripting proficiency in Python and Bash

Ideally:

• Experience with multi-environment or multi-tenant deployment architectures
• Background in regulated environments (government, defence)
• Familiarity with GPU infrastructure and ML workload scheduling
• Experience with K3S or lightweight Kubernetes distributions for edge deployments
• Knowledge 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 encounter
• Strategic impact: The Deployment team is central to our defense expansion, directly enabling new customer segments and contract opportunities
• Customer-facing work: Travel to customer sites and see your infrastructure running in real operational environments
• Growth trajectory: Join ahead of our Series B as we scale the team and expand into new markets
• Strong technical culture: Work alongside platform, ML, and GIS engineers solving novel infrastructure challenges
• Healthy work-life balance with flexible working arrangements
• Competitive compensation with personalized benefits including learning opportunities, mental well-being programs, and healthcare
• Permanent employment: no B2B option possible

Tech Stack

• Linux, Docker, Kubernetes (EKS, K3S)
• AWS, Azure, GCP
• Terraform
• Azure DevOps, ArgoCD, Helm
• Prometheus, Grafana
• Elasticsearch, Kibana
• Redis, PostgreSQL
• Python, Bash