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Forward Deployed AI Engineer
Forward Deployed AI Engineer
The Forward Deployed AI Engineer will build and deploy AI-powered workflows for defense and intelligence customers using ICEYE's intelligence platform. This hands-on role involves deploying into secure environments, developing RAG systems, and integrating SAR imagery with intelligence reports to create mission-critical tools for analysts.
About the role
About the Role
As a Forward Deployed AI Engineer, you will be the hands-on AI builder for defense and intelligence customers, deploying ICEYE’s intelligence platform into secure (often air-gapped) environments and rapidly shipping AI-powered workflows. This role involves everything from Docker-based deployments to RAG systems fusing SAR imagery with intelligence reports, turning raw satellite data into mission-critical tools for analysts.
Responsibilities
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.
Requirements
Must-Have Skills
- 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.
Nice-To-Have Skills
- 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).