Senior AI Systems Engineer - Advanced Concepts
About this role
This role addresses the need to accelerate advanced aircraft development within the field of electric aviation by building sophisticated, AI-enabled engineering systems. The Senior AI Systems Engineer will be responsible for architecting and guiding these systems, connecting domain knowledge, data, and workflows to provide practical intelligence for critical decision-making across requirements, design, analysis, and testing phases. The core mission is to translate complex engineering processes into functional AI capabilities that improve the speed and quality of aircraft development.
The engineer will focus on developing the technical roadmap for AI decision-support systems. This involves creating agents, data pipelines, and evaluation frameworks to ensure the AI outputs are accurate, robust, and reliable for safety-critical applications. Key contributions include establishing methods for verifying model accuracy, managing data provenance, and deploying these capabilities into production environments.
Candidates who excel in bridging the gap between complex engineering domains and advanced machine learning systems will thrive in this role. Success requires a strong ability to define system architecture, integrate diverse data sources, and communicate technical uncertainty clearly to both engineering teams and leadership.
What you will do
- Architect the technical roadmap for AI-enabled engineering and program decision-support systems.
- Translate engineering workflows, including requirements, design, analysis, and testing, into functional AI capabilities.
- Design and implement AI agents, retrieval services, APIs, data pipelines, and deployment infrastructure.
- Establish rigorous evaluation and verification methods to assess AI accuracy, robustness, and latency.
- Integrate controlled engineering data while maintaining necessary access control, configuration provenance, and auditability.
- Develop AI features that synthesize technical evidence, identify risks, automate tasks, and enhance the speed of development decisions.
- Coordinate with various stakeholders, including domain engineers, AI/ML roles, and legal teams.
What you need
- A Bachelor’s degree in a technical field such as computer science, machine learning, or aerospace engineering is required.
- Candidates must possess five or more years of experience delivering AI, machine learning, or complex systems into production.
- Demonstrated experience integrating models, agents, retrieval mechanisms, APIs, data pipelines, and enterprise data sources is necessary.
- Strong software development skills in Python or an equivalent language, coupled with experience in cloud deployment, containers, and automated testing.
- Proven ability to define practices for model evaluation, access control, data provenance, security, and failure handling.
- The ability to clearly articulate technical limitations, uncertainty, and recommendations to engineering and program leadership is essential.
- The role requires the ability to explain technical limitations and residual risk to stakeholders.
Nice to have
- 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
- Experience with retrieval-augmented generation
- Experience with model evaluation
Benefits
- Restricted Stock Units (RSUs) and Performance Stock Units (PSUs)
- Onsite healthcare in Vermont
- Comprehensive medical coverage
- Dental and vision coverage
- Short- and long-term disability
- Paid parental leave
- Daily lunch provided
- Flight lessons included
Skills and tech stack
Questions candidates ask
Is this role fully remote?
Remote candidates may be considered for a hybrid role, which includes monthly visits to the South Burlington, VT office for in-person work.
What is the compensation range for this position?
The listed salary for this position is between $175,000 and $200,000 USD.
What is the required technical background?
Candidates need strong software development skills in Python or an equivalent language, along with experience in cloud deployment and containers.
What kind of team structure is involved?
The role requires coordinating with domain engineers, the AI/ML and Computational Design roles, BETA OS, IT, cybersecurity, and legal stakeholders.
The application is on the official BETA Technologies careers page.
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