Forward Deployed AI Engineer

• Platform Deployment & Integration: Deploy ICEYE's intelligence platform into customer secure environments (on-premise, air-gapped networks, classified data centers)
• Build and maintain containerized applications (Docker) and manage deployments in customer Kubernetes clusters
• Develop APIs and data pipelines connecting ICEYE systems to customer C4ISR infrastructure and intelligence tools
• Troubleshoot deployment issues in disconnected environments without external internet access
• AI Solution Development & Customization: Build Retrieval-Augmented Generation (RAG) systems that combine ICEYE SAR data with customer intelligence documents for context-aware analysis
• Develop AI agents and workflows using frameworks like LangChain, LangGraph, or similar tools to automate analytical tasks
• Implement prompt engineering strategies and conversational AI interfaces that enable analysts to query satellite data using natural language
• Create Model Context Protocol (MCP) integrations connecting AI systems with customer data sources
• Data Fusion & Intelligence Workflows: Build data fusion pipelines combining SAR imagery with additional intelligence sources (AIS, RF signals, optical imagery, SIGINT)
• Develop automated workflows that correlate and cross-reference information across different data modalities
• Create lightweight tools, dashboards, and alerting systems tailored to customer operational needs
• Customer Engagement & Rapid Prototyping: Work embedded with intelligence analysts, data scientists, and military operators to understand mission-critical problems
• Rapidly prototype AI-powered solutions (code first, polish later) that address immediate operational requirements
• Conduct hands-on training sessions on platform capabilities and AI workflow usage
• Gather customer feedback and translate it into technical requirements for ICEYE's product and engineering teams

• 3+ years hands-on software engineering building and deploying production systems
• Strong Python programming skills (required) plus one of: Go, TypeScript, or Rust
• Hands-on experience with LLMs, prompt engineering, and RAG systems
• Working knowledge of agent frameworks (LangChain, LangGraph, pydantic-ai) and vector databases
• Experience with Docker and deploying in secure / isolated / air-gapped environments
• Practical experience with APIs, data pipelines, and integrating systems in production
• Familiarity with Linux and basic Kubernetes operations
• Builder mindset: ship fast, iterate with feedback, and prioritize working solutions over perfect architecture
• Strong communication + customer engagement, able to work embedded with intelligence analysts / 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

• Experience in defense, intelligence, or government operational environments
• Deploying to on-prem data centers and/or air-gapped networks
• Familiarity with geospatial data, satellite imagery, or remote sensing
• Experience with MCP integrations, multi-agent systems, or agentic workflows
• Deeper Kubernetes, IaC (Terraform/Ansible), and/or offline CI/CD
• Understanding of intelligence analysis workflows and defense/government requirements
• Experience with data fusion, multi-source intelligence integration, or GIS tools (ArcGIS, QGIS)
• Background in solution engineering, technical consulting, or customer success
• Experience in defense tech (e.g., Palantir, Anduril, Scale AI, similar startups)

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