AI Engineers in the United States.
LLM applications, RAG, agent systems, ML production infrastructure, and AI applied to engineering workflows — vetted engineers and firms nationwide.
America's directory for AI engineers.
AI engineering combines machine learning, software engineering, and product judgment — building the data pipelines, training jobs, inference stacks, RAG systems, and agent platforms that actually ship to users.
EngineerMint lists AI engineers, ML platform engineers, and firms shipping production LLM and agent systems across SF, Seattle, NYC, Boston, Austin, and beyond. For AI applied to safety-critical engineering domains, we also list cross-disciplinary P.E.s with domain experience.
Post an AI engineering scope to the marketplace, or run the AI Estimator for a ROM cost on prototype-to-production work.
Real licensed engineers, sourced from official boards
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Frequently asked questions
What does an AI engineer do?+
AI engineers build production machine-learning and LLM systems — data pipelines, training, fine-tuning, evaluation, inference infrastructure, prompt and agent design, RAG, and ML observability.
Do AI engineers need a P.E. license?+
No formal license exists for AI work today. For AI applied to safety-critical engineering (autonomous vehicles, medical devices), the deliverable still rides on a licensed P.E. or PMA-equivalent in the domain.
What credentials matter for AI engineers?+
Beyond a CS or engineering degree, look for hands-on ML production experience, certifications from AWS/GCP/Azure ML tracks, and contributions to public ML/RAG/agent projects.
What does an AI engagement typically cost?+
Prototype builds: $25k–$150k. Production RAG or agent platforms: $150k–$1M+. Foundation-model fine-tuning and dedicated inference: highly variable based on data, scale, and ongoing compute.
Can I post an AI engineering project?+
Yes. Describe the use case, data sources, and integration targets — qualified AI engineers and firms will respond.