Chief Engineer, Artificial Intelligence and Autonomy

Boeing•El Segundo, CA

About The Position

At Boeing’s Space Mission Systems, we innovate and collaborate to advance connectivity for a better world. We are committed to fostering an environment for every teammate that is welcoming, respectful, and inclusive, with exceptional opportunity for professional growth. Find your future with us. SMS is seeking a Chief Engineer, Artificial Intelligence and Autonomy to lead the establishment, growth, and operational maturation of the enterprise AI function across the full portfolio of SMS programs in Seal Beach or El Segundo, CA. This is a newly created management position responsible for increasing the adoption and integration of AI capabilities throughout SMS engineering programs, manufacturing operations, and flight systems. This Chief Engineer will define and execute the Company’s AI strategy across strategic domains including manufacturing intelligence, constellation autonomy, spectrum orchestration, and AI-assisted engineering. The role reports to Engineering VP and Space Missions Systems Chief Engineer, with a dotted-line report to the VP of Program Management and cross-functional authority across Engineering, Flight Operations, and Manufacturing.

Requirements

Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement
5+ years of experience building and leading artificial intelligence/machine learning organizations from inception, including hiring, budgeting, infrastructure provisioning, and delivery of production machine learning systems
Experience with cross-functional leadership working with different organizations and operations teams
Experience developing artificial intelligence/machine learning strategies including business case development, TRL (Technology Readiness Level) assessment, and technology transition planning

Nice To Haves

Active TS/SCI clearance
10+ years of experience collaborating with and influencing senior management and executive leadership across engineering, operations, and program management functions
Experience with physics-informed machine learning, custom ML models for hardware systems, and AI deployment in safety-critical or mission-critical environments
Experience with satellite communications, phased array antenna systems, digital beamforming, or comparable complex RF/signal processing systems
Bachelor’s degree or higher in Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical field
Excellent stakeholder management skills including the ability to communicate with and influence people from varying backgrounds, including members of senior leadership teams
Experience in aerospace and defense satellite programs (constellation management, payload engineering, launch operations)
Experience with AI-assisted software development tools, autonomous coding agents, and agentic AI workflows in engineering environments
Experience with manufacturing AI including computer vision quality inspection, predictive maintenance, and factory digital twins
Background in space edge computing, flight inference systems, onboard ML, and flight computer architectures for space applications, including TRL maturation of compute hardware
Experience with ASIC/custom silicon architectures and understanding of how DSP hardware intersects with ML inference workloads
Background in AI product development for telecommunications or enterprise customers
Experience with AI conversational interfaces, multimodal AI systems, or AI safety evaluation frameworks
Published research, patents, or demonstrated IP creation in AI/ML, autonomy, or space systems

Responsibilities

Enterprise AI Strategy & Program Coordination: Develop and maintain a comprehensive enterprise AI strategy that increases the use of AI across the full portfolio of SMS programs, serving as the primary coordinator between programs and engineering leadership
Define and present the enterprise AI roadmap to Segment Leadership, the VP of Program Management, and the executive leadership team, including business case definition, value propositions, technology readiness level (TRL) reduction plans, and program on-ramp strategies for AI-assisted engineering and space edge compute
Coordinate between SMS programs and engineering organizations on the adoption and deployment of AI-assisted coding tools and autonomous software agents to accelerate development velocity and reduce engineering cycle times
Identify, evaluate, and manage strategic AI partnerships, vendor relationships, and technology acquisitions that accelerate the Company’s AI capabilities
Mature and facilitate the intake, qualification, and prioritization of AI, analytics, and automation projects across programs, ensuring the right problems are addressed with executive sponsorship
Organizational Design & Team Building: Establish the AI & Autonomy function as a new organizational capability from the ground up, defining structure, operating model, and governance
Recruit, hire, and lead a cross-functional AI team spanning AI/ML engineers, data engineers, data scientists, MLOps engineers, and domain specialists
Build and manage an independent AI budget, compute infrastructure (GPU clusters), tooling, and vendor partnerships
AI-Assisted Engineering & Autonomous Agents: Drive the adoption of AI-assisted coding and autonomous agents across SMS engineering programs, enabling engineers to leverage generative AI, code copilots, and agentic workflows for design, analysis, and verification tasks
Develop the business strategy, TRL reduction roadmap, and program on-ramp plans for integrating AI into engineering workflows and space edge compute flight systems, from concept through flight qualification and operational deployment
Facilitate discovery workshops with engineering and program leaders to define problems, quantify value, and scope AI solutions across the portfolio
Factory AI Automation & Manufacturing Intelligence: Lead development and deployment of AI automation for factory processes, including photographic and computer vision–based quality inspections of satellite components and assemblies
Implement AI-driven engineering buy-off automation, accelerating verification and validation across integration and test workflows through autonomous review and decision support
Deploy autonomous research capabilities enabling AI-assisted document analysis, anomaly flagging, and compliance verification across satellite build records and End Item Data Packages (EIDPs)
Deliver a fully integrated Factory Product Assurance Automation Platform supporting satellite production at scale
Flight Edge Computing & Machine Learning: Create and own the business strategy, TRL reduction plan, and technology maturation roadmap for AI-assisted engineering of space edge compute systems, flight inference processors, and onboard machine learning architectures—from early concept through flight qualification and operational deployment
Define hardware architecture for space edge compute, onboard storage, and flight inference systems, enabling AI-driven data store-and-forward, real-time ML inference, and autonomous decision-making capabilities on operational satellites
Develop and deploy ML models for constellation scheduling optimization, including beam allocation, power management, thermal budget optimization, and coverage planning
Close the sim-to-reality gap by using on-orbit performance truth data to continuously improve predictive models and feed insights back into factory integration and test procedures
Spectrum Orchestration & Autonomous Operations: Develop and deploy AI-driven dynamic interference mapping and avoidance protocols across the constellation’s operating spectrum, leveraging physics-informed models validated against on-orbit telemetry
Build AI-optimized beam-hopping and resource scheduling systems that dynamically allocate spectrum and power resources based on real-time demand, interference conditions, and orbital geometry
Deliver the integrated Spectrum Allocation Orchestration Platform as an operational system managing dynamic spectrum access across the commercial constellation
Cross-Functional Integration & Stakeholder Engagement: Operate with cross-functional authority across Engineering, Flight Operations, Manufacturing, and Product to embed AI into existing workflows, coordinating with the VP of Program Management to align AI initiatives with program schedules and milestones
Establish standing technical syncs with Engineering, Flight Operations, and Manufacturing leadership to ensure AI initiatives are validated against domain expertise before deployment
Lead stakeholder communications covering AI strategies, program status, and value delivery across SMS leadership and program teams
Create materials and media to convey AI strategies and product value, including presentations, demonstrations, visual diagrams, and technical briefings
Position AI as an amplifier of existing engineering capabilities—not a replacement—ensuring adoption is collaborative and trust-based across the organization