Job Description Summary

Job Description

Company Overview

Working at GE Aerospace means you are bringing your unique perspective, innovative spirit, drive, and curiosity to a collaborative and diverse team working to advance aerospace for future generations. If you have ideas, we will listen. Join us and see your ideas take flight!

Site Overview

Established in 2000, the John F. Welch Technology Center (JFWTC) in Bengaluru is our multidisciplinary research and engineering center. Engineers and scientists at JFWTC have contributed to hundreds of aviation patents, pioneering breakthroughs in engine technologies, advanced materials, and additive manufacturing.

Role Overview:

• Find, interpret, and merge data sources, ensure dataset consistency, create visualisations, and communicate insights simply — using AI-augmented tooling (Claude Code, GitHub Copilot, LLM analytics assistants) to accelerate exploration and narrative generation.
• Prioritise, prototype, design, build, test, and deploy analytics models and AI agents in an agile methodology — including RAG on enterprise data, natural-language querying, and LLM-driven data quality and anomaly detection.
• Develop analytic/AI solutions from various source systems— augmented with AI-assisted profiling, entity resolution, and quality-check pipelines.
• Develop technical expertise in AI development for engineering applications— including next-generation 'ask-the-data' experiences powered by LLMs on top of the enterprise Data Fabric.
• Present project plans, technical roadmaps, risks, and recommendations to senior leaders — including AI/analytics adoption roadmaps tied to measurable business KPIs.
• Work closely with the Engineering teams and AI leadership to identify AI-enabled analytics use-cases (agents, copilots, conversational dashboards); translate AI-driven insights into business language for non-technical stakeholders.
• Serve as a technical specialist in the discipline — deep expertise in classical analytics and applied AI/ML for enterprise data.
• Partner closely with FLIGHT DECK and business-defined priorities to build, scale, and industrialise AI-powered analytics workflows, agents, and connectors — end-to-end to production adoption.
• Define and enforce enterprise-grade AI standards, guardrails, and best practices — responsible AI, evaluation, security, observability — so AI-powered insights are trustworthy and production-grade.
• Coach and enable AI Builders across the analytics community: teach AI Foundations, review agents/workflows, unblock architectural barriers, and align team practices with Data Fabric standards.
• Develop communication, training, and change-management deliverables to increase adoption of analytics and AI capabilities; establish a community of practice around AI-augmented analytics.

Ideal Candidate:

• Ideal candidate should have experience in SQL/Python fundamentals plus fluency in AI-augmented development — using AI as a productivity multiplier without compromising data correctness, lineage, or governance.

Required Qualifications:

• Bachelor's in Engineering/Technology/Aerospace or "STEM" Majors with a minimum of 8 years of experience.
  
• Strong oral and written communication skills; strong interpersonal and leadership skills.
• Demonstrated ability to lead programs and projects — document, plan, market, and execute end-to-end; established project-management skills.
• Demonstrated ability to analyse and resolve problems — including framing ambiguous business questions as AI/analytics problems and back.
• Strong SQL/Python fundamentals plus fluency in AI-augmented development — using AI as a productivity multiplier without compromising data correctness, lineage, or governance.
• Hands-on with modern AI development tooling: GitHub Copilot, Claude Code, LLM orchestration frameworks, agent frameworks, vector databases, and RAG patterns applied to enterprise data.
• Deep experience building secure and scalable enterprise AI-analytics solutions — deploying connectors, agents, and artifacts that enable others to scale AI adoption.
• Cloud proficiency (AWS, GCP, Azure) with data-engineering fundamentals and cybersecurity awareness.
• Coaching mindset (aligned with the AI Coach persona) — comfortable teaching AI Foundations and lifting the AI capability of analysts and engineers around you; can support ~6–8 AI Builders.
• Continuous learner who keeps pace with external AI/analytics capabilities and brings insights back to shape enterprise standards and Data Fabric alignment.
• Formal AI/ML certifications a plus — AWS Certified ML, GCP Professional ML Engineer, Azure AI Engineer, Databricks ML.

At GE Aerospace, we have a relentless dedication to the future of safe and more sustainable flight and believe in our talented people to make it happen. Here, you will have the opportunity to work on really cool things with really smart and collaborative people. Together, we will mobilize a new era of growth in aerospace and defense. Where others stop, we accelerate.

Additional Information