Legion Intelligence
Forward Deployed Engineer (D.C Area)
$160K–$200K
Washington D.C. · Full-time · Posted Jul 22, 2026
- Experience
- 4+ years in Forward Deployed Engineering, Solution Engineering, or similar customer-facing technical roles; 4+ years supporting military, intelligence, or defense-related environments.
- Visa sponsorship
- Only U.S. citizens may be hired due to government contract requirements.
About the job
Build and deploy custom applications and agentic AI workflows embedded with customers in classified or constrained environments, translating mission needs into practical systems and feeding product insights back to engineering.
What you'll do
- Understand customer mission workflows and build, prototype, deploy, and support custom applications and workflows.
- Translate user needs into technical implementations and integrate solutions with enterprise systems.
- Gather product feedback and collaborate with product and engineering teams on platform improvements.
What they ask for
- Active U.S. Department of Defense or Intelligence Top Secret (TS) clearance; SCI eligibility is required only for the SCI portion.
- U.S. citizenship.
- 4+ years in Forward Deployed Engineering, Solution Engineering, or similar customer-facing technical roles; 4+ years supporting military, intelligence, or defense-related environments.
- Experience shipping full-stack applications or prototypes; proficiency in Python, JavaScript/TypeScript, or similar scripting languages.
Nice to have
- Experience in classified or restricted environments; familiarity with mission domains such as operations, logistics, intelligence, or C4/IT systems.
- Experience deploying AI/ML systems, especially agentic workflows, or familiarity with n8n, Palantir Foundry, or other workflow/automation platforms.
Pay
$160,000 — $200,000 USD (base salary)
Tools
Python, JavaScript/TypeScript, Microsoft O365, Palantir Foundry, Databricks, ServiceNow, Atlassian, Node.js
AI focus
Rapidly prototype and iterate on agentic AI solutions and workflows; preferred experience includes building or deploying AI/ML systems and evaluating AI system performance.
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