Sr. Director, AI Architecture

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Job Description Summary The AI Architect is the senior technical leader for the team building AI enabled engineering capabilities across the business organizations of an aero engine and propulsion OEM. The role sets the reference architecture, selects and sequences the use cases worth pursuing, validates feasibility through proof of concept builds, and leads and coaches the engineers who deliver them, ensuring everything the team ships is deliverable inside aerospace constraints on data, security, and export control. It pairs hands on technical ownership with the second line leadership, operating plan and budget ownership, and governance responsibilities of the Sr. Director, Architecture (SPB1) standard, with five AI Engineers, one aligned to each business, as direct reports (growing to include team leads), and the mandate to grow the function as the portfolio expands. Deep credibility in the physics and engineering of the product, turbomachinery, aerodynamics, combustion, heat transfer, structures, and materials, and a product mindset shaped by certified, safety critical hardware are core to the role; AI is applied to challenging propulsion and turbomachinery engineering problems across design, analysis, test, manufacturing, and sustainment, not treated as a specialty unto itself. Job Description In this role, you will: Lead and coordinate the technical and business discussions on future AI architectural direction across multiple teams and complex product lines, anchored to real propulsion and turbomachinery engineering problems. Analyze, design, and develop a roadmap and implementation plan for AI enabled engineering capabilities based on a current vs. future state, in a cohesive architecture viewpoint aligned to the digital thread. Review, analyze, and develop architecture at the domain level and across multiple teams, reference architectures for data pipelines, model and agent deployment, evaluation, and integration with PLM and existing simulation and analysis toolchains. Ground the reference architecture in the realities of aero engine, propulsion, and turbomachinery engineering, design, analysis (CFD, FEA, thermal and structural), test, manufacturing, and sustainment, defining how AI integrates with model based systems engineering, the digital thread, PLM, engine and rig test data, and the existing simulation toolchains. Participate in the enterprise architecture domain governance model, and define the AI governance, security, and export control posture (ITAR / export control, CMMC, RMF / ATO) so solutions are compliant by design across classified and unclassified environments. Contribute to the development of software, data, and technology platforms with reusable components across teams that can be orchestrated together, capturing reusable patterns, libraries, and reference implementations from each delivery. Lead the research and evaluation of emerging AI technology, industry, and market trends (LLM and retrieval augmented generation, vector databases, agentic orchestration) to inform development and operational support across multiple teams; run proof of concept builds to validate architectural and physical assumptions, including where physics informed or surrogate modeling of engine analysis (CFD/FEA/thermal) is appropriate versus where it is not, before committing the team. Set model and agent lifecycle practice: evaluation against engineering ground truth, versioning, monitoring, drift detection, retraining triggers, and rollback. Provide leadership, technology guidance, and mentorship throughout the domain; provide architecture direction to the embedded AI Engineers, review their designs, and remove technical blockers to keep delivery moving. Be a technical leader within the function and develop and coach the technical resources within it; serve as the single technical interface to enterprise platform, data, and security functions. Influence from a strategic and technical standpoint across the function and the business; present business and technical discipline solutions to senior leaders, communicate complex messages, and negotiate internally and with external partners, vendors, and customers to align on direction, tradeoffs, feasibility, and risk. Own and influence the budget and operating plan for the AI engineering function; provision and budget via capital and operating, and manage financials across programs and projects. Develop peer, cross functional, and cross business relationships to maximize best practice sharing and team effectiveness. Be responsible for management activities including recruiting, development, performance management, compensation, organization, and teaming. Lead the AI Engineering team, five AI Engineers, one aligned to each business, plus team leads as the function scales toward second line management, with the ability to attract, develop, and retain talent and to grow the team as the portfolio expands. Share technical, procedural, and business knowledge with oth

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Company Intel

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