Forward-Deployed ML Engineer for National Security

Adelphi Data; McLean (VA); Hybrid; USD 140,000 - 180,000; Full time

Job summary

Adelphi is seeking a Machine Forward Deployed Learning Engineer to join our AI-native engineering team. You will develop full-stack, agentic systems on frontier models, embedded alongside defense and intelligence customers in a hybrid DC/Metro setting.

You should be proficient with LLM tooling, secure deployment practices, and cross-cutting software layers from OS to API. An active U.S. Government clearance is required to collaborate with our partners.

Qualifications

• Active U.S. Government clearance required.
• Experience in defense or intelligence fields is required.
• Hybrid work model with three days in office in the DC/Metro area.

Responsibilities

• Deliver end-to-end agentic, full-stack systems from prototype to production.
• Build ML services using LLMs, embeddings, RAG, and agent orchestration.
• Collaborate with customers to understand problems and guide delivery.
• Create reusable tools and building blocks to speed up ship rate.

Skills

AI tooling

LLM lifecycle

Agent frameworks

LLM integration frameworks

AI limitations awareness

Tools

LangGraph

OpenAI Agents SDK

Claude Agent SDK

AutoGen

MCP

Job description

Adelphi is seeking a Machine Forward Deployed Learning Engineer to join our AI-native engineering team. You will develop full-stack, agentic systems on frontier models, embedded alongside defense and intelligence customers in a hybrid DC/Metro setting.

You should be proficient with LLM tooling, secure deployment practices, and cross-cutting software layers from OS to API. An active U.S. Government clearance is required to collaborate with our partners.