Senior Staff Engineer - AI

Role overview

Senior Staff Engineer - AI at GE Aerospace

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.

Responsibilities

• You will design and deliver AI frameworks which can be scaled across the enterprise, and leverage LLMs, agents, and RAG to unlock measurable business KPIs.
• Develop analytic/AI solutions from various source systems— augmented with AI-assisted profiling, entity resolution, and quality-check pipelines.
• 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.

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.

Employment details

• Location: Bengaluru [Karnātaka] [India]

Additional role details

• As a Senior AI Engineer , you will combine deep classical analytics craft, data engineering, with modern AI-native ways of working.
• You will partner closely with FLIGHT DECK, publish AI workflows and agents, and help raise the AI capability of the analytics community around you as an emerging AI Coach.
• 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 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.
• 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.
• 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.
• Here, you will have the opportunity to work on really cool things with really smart and collaborative people.