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The Aerospace Corporation

Lead AI Engineer

Posted Yesterday
Be an Early Applicant
Hybrid
Phoenix, AZ
Senior level
Hybrid
Phoenix, AZ
Senior level
Lead the development of physics-informed AI, surrogate, and digital twin models for aerospace engineering design and simulation. Drive AI strategy, research multi-physics methodologies, and integrate models with CFD, FEA, thermal, and systems workflows. Lead internal and government-sponsored R&D projects, support proposals, collaborate with engineering and research teams, and mentor AI engineers and researchers.
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As a Lead AI Engineer at Honeywell Aerospace, you will provide expert-level technical leadership in the development of AI-driven engineering design tools and physics-based machine learning models. This role focuses on applying artificial intelligence, physics-informed methods, and surrogate modeling to accelerate the design and analysis of aerospace mechanical systems, including engines, wheels and brakes, environmental control systems, and other complex components. You will help shape the next generation of simulation and analysis capabilities by integrating AI with traditional computational tools such as CFD, FEA, and multi-physics solvers.

In this role, you will craft and lead multi-year research strategies, develop advanced AI surrogates and Physics-AI models, and transition these technologies into engineering workflows across Honeywell Aerospace. You will collaborate with cross-functional teams and global research partners, pursue both internal and government research funding, and guide execution from concept through integration. Your work will significantly impact engineering efficiency, product performance, and Honeywell Aerospace 's leadership in AI-enabled engineering design.

You will report directly to the manager of the AI Research Group and work from our Phoenix, AZ location on a hybrid schedule.

Responsibilities

Key Responsibilities 

• Lead development of advanced Physics-AI models and surrogate models to accelerate engineering workflows for CFD, thermal analysis, structural analysis, and system-level simulation.
• Define and drive the AI strategy for engineering design, with a focus on physics-informed neural networks (PINNs), digital twins, and high-fidelity model surrogates.
• Research, develop, and validate new AI methodologies for multi-physics modeling of aerospace components such as engines, wheels and brakes, and mechanical actuation systems.
• Utilize and advance state-of-the-art NVIDIA simulation and AI acceleration tools, including Physics NEMO and related model‑based AI frameworks.
• Collaborate closely with engineering teams to integrate surrogate models into design processes, enabling faster trade studies, optimization, and predictive analysis.
• Lead technical execution across internal and government-sponsored R&D projects and contribute to proposal development.
• Mentor AI engineers and researchers, fostering excellence, innovation, and deep technical growth.

 
Qualifications

US PERSON REQUIREMENT

Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.

You Must Have
• Bachelor’s or Master’s degree in aerospace engineering, mechanical engineering, or a related engineering discipline.
• Minimum 5 years of experience developing AI models for physics-based simulation, engineering analysis, multi-physics modeling, or surrogate modeling.
• Minimum of 10 years working on design and simulation of physics of engineering systems involving concepts such as Computational Fluid Dynamics or Structural Analysis 

• Experience leading technical teams and mentoring junior engineers.

• Expert level expertise with NVIDIA’s physics‑accelerated AI tools such as Physics NEMO, Modulus, Warp, or similar platforms for physics-informed deep learning

We Value
• Proficiency in Python and machine learning frameworks such as PyTorch and TensorFlow.
• Experience working in structured machine learning deployment environments i.e. MLOps workflows

• Deep knowledge of CFD, structural analysis, thermal modeling, or multi-physics simulation, and the ability to couple these with AI-based surrogates.
• Experience deploying AI models into engineering design workflows or digital engineering ecosystems.
• Strong understanding of current research in physics-informed ML, scientific machine learning, and surrogate modeling at major conferences and journals.

About us:

Join a company that's reintroducing itself to the aviation community we've helped advance for more than a century. At Honeywell Aerospace (NASDAQ: HONA), we're launching as an independent, publicly traded aerospace and defense company built on a legacy of operational excellence and mission-focused execution. 

Our new brand identity pairs that heritage with real momentum, as we build technology that helps pilots navigate with confidence, aircraft operate more efficiently, and operators stay ahead of change. With our systems on board 90% of the world's aircraft, your work here has reach that's rare to find anywhere else.

Focusing on our customers, investing in innovation, and building a culture of accountability and performance is how we're shaping what comes next.

Every horizon. Every mission. Every day.

Benefits:

Beyond a performance-driven salary, you'll work alongside dedicated experts on technology that's advancing aviation. As a Honeywell Aerospace employee, you're eligible for a comprehensive benefits package that includes:

  • Employer-subsidized medical, dental, vision and life insurance
  • Short-term and long-term disability coverage
  • 401(k) match, flexible spending accounts and health savings accounts
  • Employee assistance program and educational assistance
  • Parental leave and 12 paid holidays
  • Paid time off for vacation, personal and sick time

Explore your benefits: https://honeywellaerospacebenefits.com/

POSTING TIMELINE

The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.

The Aerospace Corporation Colorado Springs, Colorado, USA Office

7250 Getting Heights, Colorado Springs, CO, United States, 80916-4931

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