Senior Staff Applied AI Engineer - Engineering Systems

Lockheed Martin•Fort Worth, TX

19h•Onsite

About The Position

What if your work could help prevent conflict, by making our capabilities so advanced, no one dares to challenge them? We are the Aero Artificial Intelligence team at Lockheed Martin Aeronautics, building and deploying trusted AI that strengthens deterrence, improves engineering rigor, and advances global security. This role is for a senior, hands-on AI professional who operates with high independence and technical ownership. You will design and deliver AI systems that improve how complex aerospace systems are engineered, integrated, tested, and sustained. Understanding aerospace systems engineering is valuable, but deep AI expertise and autonomous execution are paramount. Job Description The Senior Applied AI Engineer - Engineering Systems is responsible for independently framing, architecting, and delivering AI-enabled solutions that improve systems engineering effectiveness, safety, and efficiency across the engineering lifecycle. This role operates as a technical authority within the scope of AI projects, leading end-to-end development from problem definition through deployment. The engineer partners closely with systems engineering, integration and test, and program stakeholders, translating ambiguous engineering challenges into impactful AI solutions. The position is functionally aligned within Aero AI and supports multiple programs and engineering organizations, enabling scalable AI adoption across the enterprise.

Requirements

Demonstrated experience applying AI/ML to real-world engineering or scientific problems
Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Experience designing and delivering AI systems end-to-end with minimal oversight
Background in systems thinking, model-based engineering concepts, or digital thread workflows
Bachelor's or Master's degree in Engineering, Computer Science, Systems Engineering, or a related field
Ability to operate independently, frame ambiguous problems, and drive technical execution

Nice To Haves

Experience applying AI to systems integration, test, or validation workflows
Familiarity with digital twin concepts, simulation environments, or performance modeling
Experience collaborating across systems engineering and sustainment organizations
Exposure to aerospace or safety-critical engineering environments
Experience applying AI for process optimization, anomaly detection, or decision support
Familiarity with MBSE tools or structured engineering models
Experience leading small technical teams or cross-functional efforts
Understanding of DevSecOps practices, version control, and agile development
Awareness of ethical and trustworthy AI principles

Responsibilities

Independently define AI solution approaches for complex engineering and systems-level problems
Design, develop, and deploy end-to-end AI/ML solutions from data ingestion through operational use
Build AI-enabled tools supporting requirements analysis, system validation, test planning, and traceability
Apply predictive modeling, simulation, and analytics to improve digital twin alignment and performance estimation
Partner with systems engineering, integration and test, and sustainment teams to identify high-value AI use cases
Lead small, cross-functional project teams to execute AI pilots and scaled deployments
Translate engineering workflows and constraints into robust AI system architectures
Improve safety, efficiency, and engineering rigor through AI-augmented process optimization
Support integration and test organizations with AI-enabled scenario generation, anomaly detection, and data analysis
Ensure AI solutions align with ethical, cybersecurity, and operational constraints
Contribute to technical roadmaps and best practices for enterprise AI adoption