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Job Description & How to Apply Below
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 C4
ISR infrastructure and intelligence tools. - Troubleshoot deployment issues in disconnected environments without external internet access.
- 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 Lang Chain
, Lang Graph
, 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.
- 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.
- 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
, Type Script , or Rust
. - Hands‑on experience with LLMs
, prompt engineering
, and RAG systems
. - Working knowledge of agent frameworks (
Lang Chain
, Lang Graph
, 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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