Agentic AI Engineer: Automated Design Pipelines

Anduril

Costa Mesa (CA)

On-site

USD 120,000 - 180,000

Full time

6 days ago
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Job summary

Anduril is seeking an Agentic AI Engineer in Costa Mesa, CA to automate engineering workflows and build agent-powered capabilities. You will connect legacy tools to modern ML workflows and drive design iterations using agents across CFD, FEA, thermal, and electromagnetics.

This role emphasizes building end-to-end agent pipelines, tool integrations, and guardrails while mentoring engineers who are not ML specialists. Defense experience is not required.

Qualifications

  • MS or PhD in aerospace, mechanical, electrical engineering, CS, data science or ML.
  • 0–3 years of professional experience with agentic AI systems.
  • Strong Python and MATLAB skills; knowledge of Java/Go/C++.
  • Experience with Model Context Protocols and related tooling.

Responsibilities

  • Build multi-agent pipelines that compress the engineering design loop across CFD, FEA, thermal, and electromagnetics.
  • Evolve how agents interact with engineering software: tool calling, prompts, and task decomposition.
  • Automate data extraction from solvers and build dashboards for engineers and leadership.
  • Create bespoke tooling through agents for aerodynamics, thermal, GNC, structures, and avionics.
  • Choose models at each stage and optimize routing, context, and caching for efficiency.
  • Develop evaluation harnesses, guardrails, and sandboxed execution for safe deployment.
  • Mentor engineers and identify projects where agents deliver high impact.

Skills

Python
MATLAB
Java/Go/C++
ML/AI

Education

MS or PhD in aerospace / mechanical / electrical engineering, computer science, data science, or ML

Job description

Anduril is seeking an Agentic AI Engineer in Costa Mesa, CA to automate engineering workflows and build agent-powered capabilities. You will connect legacy tools to modern ML workflows and drive design iterations using agents across CFD, FEA, thermal, and electromagnetics.

This role emphasizes building end-to-end agent pipelines, tool integrations, and guardrails while mentoring engineers who are not ML specialists. Defense experience is not required.

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