Agentic AI Engineer, Automation

About the team

Air Dominance & Strike designs builds and flies autonomous air vehicles from collaborative combataircraftto 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 howengineersaccess 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 notrequired. We are looking for engineers who came to machine learning through the problems they were already trying to solve.

This role is basedonsitein our Costa Mesa CA office.

What Youll 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 MCP servers
• Experience building agentic systems including multi-agent orchestration tool calling prompt engineering integration into classical software systems and retrieval-augmented generation
• Experience with data extraction aggregation and sanitization techniques and with building production data pipelines from heterogeneous engineering and test sources
• Proficiency developing on Linux with containerized deployment via Docker and Kubernetes
• Eligible to obtain and maintain a U.S. Secret security clearance

Preferred Qualifications

• Experience deploying LLM applications in accredited or otherwise restricted cloud environments
• Experience with cost and latency optimization at scale including caching batching and prompt and context efficiency
• Experience with structured output function calling and prompt optimization at production scale
• Experience building knowledge graphs or semantic layers over engineering data
• Familiarity with engineering toolchains such as PLM systems requirements management tools solvers and test data systems

The salary range for this role is an estimate based on a wide range of compensation factors inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience education and/or training critical skills and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Andurils total compensation package. Additionally Anduril offers top-tier benefits for full-time employees including:

At Anduril we invest in our people. Our comprehensive competitive benefits package (available at little to no cost to employees) ensures youre supported in health recovery and whatever comes next.For more information Explore Our Benefits.

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