As a Senior AI Systems Engineer on the Advanced Systems team, you will architect and guide AI-enabled engineering systems that accelerate advanced aircraft development from concept through flight test. You will connect aircraft-development knowledge, data, tools, and workflows to deliver practical intelligence for requirements, design, analysis, test, configuration, and program decisions. This position will be based onsite at our South Burlington, VT office location, our Raleigh, NC office. Remote candidates may be considered for a hybrid role, with monthly visits to South Burlington, VT for in person work.

How you will contribute to revolutionizing electric aviation:

• Define the architecture and technical roadmap for AI-enabled engineering and program decision-support systems
• Translate requirements, design, analysis, test, configuration, and program workflows into AI capabilities with clear users, inputs, outputs, interfaces, and measures of success
• Architect agents, retrieval, model services, APIs, data pipelines, evaluation, observability, and deployment infrastructure
• Integrate controlled engineering data and tools while preserving access control, configuration, provenance, data rights, and auditability
• Establish evaluation and verification methods for accuracy, grounding, robustness, reproducibility, failure behavior, latency, and cost
• Develop AI capabilities that synthesize technical evidence, identify relationships and risks, automate routine work, and improve the speed and quality of aircraft-development decisions
• Coordinate domain engineers, the AI/ML and Computational Design roles, BETA OS, IT, cybersecurity, and legal stakeholders; run technical and risk reviews
• Deploy and sustain reusable capabilities; monitor performance and drift, manage changes and incidents, and guide other engineers

Minimum Qualifications:

• Bachelor’s degree in computer science, software engineering, machine learning, systems engineering, aerospace engineering, or a related technical field
• Five or more years of experience delivering AI, machine-learning, data, software, or complex systems into production, including independent architecture ownership
• Demonstrated experience integrating models, agents, retrieval, APIs, data pipelines, evaluation, observability, and enterprise data sources
• Strong software-development ability in Python or an equivalent language, with experience in cloud deployment, containers, automated testing, and source control
• Experience defining model evaluation, access control, data provenance, security, change control, and failure-handling practices
• Ability to explain technical limitations, uncertainty, residual risk, and recommendations to engineering and program leadership
• Must be a US Person to be considered for the role

Above and Beyond Qualifications:

• AI or digital-engineering experience in aerospace or another regulated or safety-critical product environment
• Experience integrating requirements, 3DX, CAD, CAE, test, configuration, or engineering knowledge systems
• Experience with multi-agent systems, retrieval-augmented generation, model evaluation, technical knowledge systems, or engineering decision support

Physical Demands and Work Environment:

This role requires extended computer work and regular interaction with office, laboratory, manufacturing, hangar, aircraft, and test environments. Occasional travel, nonstandard test support, and use of required personal protective equipment may be necessary.