Agentic AI Engineer, Automation

Anduril; Costa Mesa (CA); On-site; USD 120,000 - 180,000; Full time

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 Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century's most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril's family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century's most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril's family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

About the team

Air Dominance & Strike designs, builds, and flies autonomous air vehicles - from collaborative combat aircraft to expendable cruise missiles to counter-UAS interceptors. Our vehicles move from whiteboard to first flight on timelines that traditional primes consider impossible, which means our design cycles live or die on how fast we can close the iteration loop and begin testing. The Anduril AI-Engineering team exists to collapse that loop.

We are engineers first. We work from engineering first principles and unlock capability through machine learning. We are building to scale across design, analysis, test, and program execution, with agent pipelines and tooling that carry across programs.

About the job

We are looking for an Agentic AI Engineer to automate engineering workflows, build new capability through agents, and improve how engineers access and act on their data. Our R&D work runs through tools of varying fidelity, from empirical methods and low-order models to high-fidelity solvers. You will chain those tools into automated flows that carry a design through analysis to build and then back into the next iteration.

You will own agent pipelines end to end: orchestration logic, tool and data integrations, evaluation harnesses, and guardrails. Much of the work is getting agents to drive legacy engineering software which were built for human operators rather than programmatic control. You will also use agents to build new tools as programs evolve and requirements change, standing up capability on program timelines rather than software release cycles.

Defense experience is not required. We are looking for engineers who came to machine learning through the problems they were already trying to solve.

This role is based onsite in our Costa Mesa, CA office.

What You'll Do

• Build and deploy multi-agent pipelines that compress the engineering design loop, including automated case setup, batch submission, and post-processing of solver runs across CFD, FEA, thermal, and electromagnetics
• Design, implement, and evolve how agents interact with classical engineering software: tool calling, prompt engineering, task decomposition, state management, retries, and human-in-the-loop checkpoints,
• Automate data extraction and aggregation across solvers, test benches, and program systems, and build the dashboards that give engineers and leadership rapid access to their own results
• Build bespoke tooling through agents for engineering sub-disciplines, including aerodynamics, thermal, GNC, structures, and avionics, that brings new capability in-house
• Choose which model to run at each stage of agent work, from planning through tool development to execution, and tune routing, context management, and caching so agents run efficiently against token cost and latency budgets
• Build the evaluation harnesses, guardrails, and sandboxed execution needed to defend agent behavior before it is deployed on a program
• Mentor engineers who are not ML specialists, and work with them to identify and scope the projects where agents deliver the highest impact

Qualifications

• MS or PhD in aerospace, mechanical, or electrical engineering, computer science, data science, or machine learning
• 0-3 years of professional experience, with demonstrated hands-on work implementing agentic AI systems
• Strong programming skills in Python and MATLAB, and working knowledge of at least one additional core language such as Java, Go, or C++
• Experience with Model Context Protocols, including building and maintaining M