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Salary: USD 175,000 - 200,000 / annual
BETA Technologies is revolutionizing electric aviation through sustainable aircraft development. As a Senior AI Systems Engineer on the Advanced Systems team, you will architect and lead AI-enabled engineering systems that accelerate aircraft development from concept through flight test.
You will serve as the technical architect connecting aircraft-development knowledge, data, tools, and workflows to deliver practical intelligence for requirements, design, analysis, test, configuration, and program decisions. This is a senior individual-contributor role with significant scope and influence across the organization.
Key Responsibilities:
- 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 success metrics
- Architect agents, retrieval systems, model services, APIs, data pipelines, evaluation frameworks, 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 decision quality in aircraft development
- Coordinate across domain engineers, AI/ML teams, Computational Design, 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 mentor other engineers
The role is based onsite at South Burlington, VT or Raleigh, NC, with hybrid arrangements possible for remote candidates requiring monthly in-person visits to South Burlington.
Requirements:
- Bachelor's degree in computer science, software engineering, machine learning, systems engineering, aerospace engineering, or related technical field
- 5+ years of experience delivering AI, machine-learning, data, software, or complex systems into production, including independent architecture ownership
- Demonstrated experience integrating models, agents, retrieval systems, APIs, data pipelines, evaluation frameworks, observability, and enterprise data sources
- Strong software-development ability in Python or 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
Preferred Qualifications:
- AI or digital-engineering experience in aerospace or other regulated/safety-critical product environments
- 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
