Mission-Driven AI Engineer for Defense & National Security

Carnegie Mellon University; Pittsburgh (Allegheny County); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Bus pass

Tuition benefits

PTO & holidays

Life & disability insurance

Retirement plan

Job summary

Carnegie Mellon University is seeking an AI Engineer to bridge research and production software, delivering mission‑scale AI capabilities for defense and national security. You will work with large foundation models, design agentic workflows, and deploy robust, secure AI systems in collaboration with government sponsors.

The role emphasizes on‑site work at CMU locations in Pittsburgh or Arlington, requiring strong Python/C++ skills, ML theory, and hands‑on experience with LLM fine‑tuning using

Qualifications

• Bachelor’s or MS in CS/ML with 5–8+ years of relevant experience.

Responsibilities

• Design, develop, and fine‑tune AI models and pipelines.
• Build autonomous agents and multi‑step workflows with LangChain or similar.
• Develop retrieval‑augmented generation pipelines with external knowledge bases.
• Implement end‑to‑end data pipelines (Python/C/C++, Java) feeding models.
• Create CI/CD pipelines for model training, deployment, and security scanning.
• Mentor junior staff and collaborate with government sponsors on reviews.

Skills

Python

C/C++

REST/GraphQL APIs

Hugging Face Transformers

LangChain

RAG pipelines

PEFT/LoRA

TensorFlow/PyTorch/JAX

ModelContext protocols

DevSecOps CI/CD

Education

Bachelor’s degree in CS/ML + 8 years

MS degree + 5 years

Tools

Docker

Kubernetes

Git

Airflow

Job description

Carnegie Mellon University is seeking an AI Engineer to bridge research and production software, delivering mission‑scale AI capabilities for defense and national security. You will work with large foundation models, design agentic workflows, and deploy robust, secure AI systems in collaboration with government sponsors.

The role emphasizes on‑site work at CMU locations in Pittsburgh or Arlington, requiring strong Python/C++ skills, ML theory, and hands‑on experience with LLM fine‑tuning using