Sr. Director, AI Architecture

AI Architect

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 use cases, validates feasibility through proof‑of‑concept builds, and leads and coaches engineers, ensuring all deliverables comply with aerospace constraints on data, security, and export control.

Responsibilities

• 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 and develop architecture at the domain level and across multiple teams, including 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 existing simulation toolchains.
• Participate in the enterprise architecture domain governance model and define the AI governance, security, and export control posture (ITAR, 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.
• Lead research and evaluation of emerging AI technology, industry, and market trends (LLM, 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.
• 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 embedded AI Engineers, review their designs, and remove technical blockers to keep delivery moving.
• 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, trade‑offs, 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 of five AI Engineers and future team leads as the function scales, attracting, developing, and retaining talent and growing the team as the portfolio expands.
• Share technical, procedural, and business knowledge with others; create learning content, give presentations, and support a continuous learning culture.

Education & Experience

• Bachelor’s degree in Computer Science or a STEM major (Science, Technology, Engineering, and Math).
• 10 years of experience, including production AI/ML systems, enterprise‑scale architecture, and leadership of technical teams.

Clearance & Security

• US person required; must be able to obtain a US security clearance. Active clearance preferred.
• Experience delivering inside aerospace & defense or comparable regulated constraints (ITAR, export control, CMMC, RMF/ATO, air‑gapped or impact‑level environments).

Desired Characteristics

• Advanced degree.
• Technical expertise: consult with business on alignment of outcomes and desired AI solutions at an enterprise level; design, roadmap, and implementation based on current vs. future state.
• Architecture experience covering model training, deployment, monitoring at enterprise scale; strong software engineering foundation, design patterns, APIs, integration approaches, cloud (AWS, Azure, GCP), containerization (Docker, Kubernetes).
• Hands‑on experience with LLM, retrieval‑augmented generation patterns, vector databases, agentic orchestration frameworks.
• Knowledge of configuration choices, cost implications, compute, model hosting, build vs. buy decisions.
• Data engineering, data governance, and assessment of data readiness for AI on messy, real engineering data.
• Experience sustaining operational stability through lifecycle phases (planning, implementation, steady state, decommissioning); MLOps lifecycle management.
• Fluency in the physics and engineering of aero engines and turbomachinery, aerodynamics, combustion, heat transfer, structures, rotordynamics, materials; judgment on physical credibility of models; familiarity with CFD, FEA, thermal/structural simulation, engine/rig test data, surrogate and physics‑informed models, digital thread, PLM.
• Business acumen: interpret internal and external business challenges, recommend best practices, stay informed of industry trends.
• Leadership: foresee obstacles, identify workarounds, leverage resources, rally teammates; lead blended teams, partners, and customers; change management; strong interpersonal skills, creativity, curiosity; influence across all organizational levels; lead without direct authority.
• Six Sigma Green Belt certification or equivalent quality certification.

Compensation

• Base pay range: $176,000 – $235,000 (specific pay influenced by experience, education, skills).
• Eligible for an annual discretionary bonus based on a percentage of base salary.

Benefits

• Healthcare: medical, dental, vision, prescription drug coverage; Health Coach; Employee Assistance Program.
• Retirement: GE Aerospace Retirement Savings Plan (401(k) with company matching and contributions).
• Additional benefits: tuition assistance, adoption assistance, paid parental leave, disability insurance, life insurance, paid time‑off for vacation or illness.

Equal Opportunity Employer

GE Aerospace is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, age, disability, protected veteran status, or any other characteristic protected by law. GE Aerospace will only employ individuals legally authorized to work in the United States for this opening.

EEO Statement

Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). The role requires U.S. export‑controlled information; therefore, employment will be contingent upon the ability to prove compliance as a U.S. Person.