Jobs at GE Aerospace

Leads the design, implementation, coaching, and continuous improvement of GE Aerospace’s FLIGHT DECK operating system across Software & Sustainability. Partners with senior leadership to translate strategy into operating cadences, standard work, daily management, KPI action plans, structured problem solving, value stream management, and SQDC improvements. Coaches leaders on lean methods, Hoshin Kanri, FUEL principles, 5S, kaizen, and leader standard work while coordinating reviews and organizational communication.

Process multi-state payroll accurately and on time, manage deductions/garnishments, ACH transfers, reconciliations with the general ledger, support audits and SOX controls, resolve employee payroll inquiries, collaborate with HR/finance/vendors, and maintain payroll systems and documentation.

The Data & Analytics Leader will develop a multi-year roadmap to enhance data governance and analytics capabilities, while fostering a data-driven culture throughout ERAC.

Lead and grow an offensive security team delivering web application pentests, Defense-in-Depth assessments, and Red Team operations. Drive an automation-first, AI-enabled program, own tooling and vendor contracts, define methodologies and KPIs, coordinate with detection/IR and product teams, and ensure prioritized remediation and continuous validation across IT, cloud, OT, and AI/ML environments.

Design, build, and ship production-grade AI and data solutions including LLM-powered applications, ML models, and APIs. Consult on architecture, own features end-to-end, support production, run design-thinking workshops, and collaborate across teams to deliver cloud-based, scalable data and AI capabilities.

Design, build, and ship production-grade AI and data solutions (LLM apps, ML models, APIs). Consult on architecture, own end-to-end features, support deployments, run design workshops, and collaborate cross-functionally to deliver cloud-based data and AI systems.

Design, build, and ship production-grade AI and data solutions (LLM apps, ML models, APIs). Consult on architecture, own features end-to-end, apply cloud and data engineering, lead design thinking workshops, and collaborate across teams to deliver measurable business impact.

Lead discovery and modernization of expert-driven manual processes using LLMs, AI agents, and automation. Embed with domain experts to extract tacit knowledge, produce formal process models, design multi-step agent workflows with HITL escalation, replace legacy tools, and build evaluation and audit frameworks to ensure safe, verifiable production deployment.