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ICEYE is seeking a Forward Deployed Backend/DevOps Engineer to serve as the backend and infrastructure backbone for defense and intelligence customers. You will deploy ICEYE's intelligence platform into secure, often air-gapped environments and design high-performance backend systems that move satellite data at scale. This is a hybrid role based in Lisbon with approximately 50% on-site time at customer locations.
You will own platform deployment and operations, installing and upgrading Kubernetes clusters and containerized applications in customer environments (both cloud and on-premises). You'll build infrastructure-as-code using Terraform and Ansible, and design CI/CD pipelines that function without external internet access, including offline registries and artifact mirroring. You'll troubleshoot deployment and production issues in disconnected environments across all layers from application to storage and networking.
On the backend systems side, you'll design and build APIs, services, and data pipelines handling large volumes of SAR imagery and intelligence data with low latency. You'll connect ICEYE systems to customer C4ISR infrastructure and intelligence tools through robust integrations, own database design and performance at production scale (PostgreSQL, MongoDB), and apply caching, queueing, and horizontal scaling patterns deliberately—with particular attention to capacity planning for fixed on-premises hardware.
Reliability and security are critical: you'll build monitoring, logging, and alerting that work in restricted environments, harden deployments to meet customer security constraints, and own backup, recovery, and upgrade paths for systems that cannot go down. You'll also run infrastructure behind AI workloads shipped by the team, including model serving, vector databases, and GPU nodes.
Customer engagement is core to the role. You'll work embedded with intelligence analysts, operators, and customer IT teams to understand operational and infrastructure requirements. You'll rapidly prototype and iterate to address immediate operational needs, conduct hands-on training for customer administrators, and feed deployment experience back to ICEYE's product and engineering teams as concrete technical requirements.
The tech stack includes Python and Go services on Kubernetes, PostgreSQL and MongoDB, Terraform and Ansible, CI/CD pipelines that run offline, cloud (AWS) and on-premises air-gapped clusters, with AI-assisted development as the default.
REQUIREMENTS:
Must-haves:
- 5+ years hands-on backend engineering building and operating production systems at scale
- Strong programming skills in Python; you write typed, tested services and are comfortable with async APIs (TypeScript is a plus)
- Proven experience designing high-performance backend systems: APIs, distributed services, messaging, caching, and databases under real load (spatial, search, or vector workloads in Postgres is a plus)
- Production experience in both cloud (e.g., AWS) and on-premises environments
- Deep Docker and Kubernetes expertise: deploy, debug, and upgrade clusters (not only consume them); GitOps and infrastructure-as-code experience; pipelines that run offline or on isolated networks are a plus
- Observability as a habit: metrics, logs, and alerts are part of done
- Infrastructure-as-code (Terraform, Ansible) and CI/CD experience, ideally including offline or isolated network pipelines
- PostgreSQL and/or MongoDB at production scale: schema design, tuning, replication, backup, and recovery
- Builder mindset: ship fast, iterate with feedback, prioritize working solutions over perfect architecture
- Strong communication and customer engagement; able to work embedded with intelligence analysts and military operators
- Strong spoken and written English; able to explain technical concepts to non-technical stakeholders
- Willingness to travel 40–60% to customer sites within the region
- Must be eligible and able to attain relevant national and NATO security clearances
- Must be based in-country and native-level speaker of Portuguese
Nice-to-haves:
- Experience in defense, intelligence, or government operational environments
- Deploying to on-prem data centers and/or air-gapped networks, including offline artifact and registry management
- Event streaming and high-throughput data systems (e.g., Kafka) at production scale
- Deeper Kubernetes: operators, service mesh, multi-cluster, storage and networking internals
- Security hardening and accreditation experience (system hardening baselines, audit and compliance in classified environments)
- Familiarity with geospatial data, satellite imagery, or remote sensing
- Experience running infrastructure for AI/LLM workloads: GPU scheduling, model serving, vector databases
- Active use of AI-assisted development tools as part of daily workflow
- Experience in defense tech (e.g., Palantir, Anduril, Scale AI, similar startups)
