Staff AI Engineer, Enterprise AI

Job Description Summary

GE HealthCare is accelerating its transformation through a series of strategic “AI Big Bets” in Commercial excellence, Logistics optimization, Inventory management, and Manufacturing innovation. The Enterprise AI team, part of the Chief Data and Analytics Office, is at the forefront of delivering robust, enterprise-grade AI and ML solutions that drive measurable business impact at scale.

As a Staff AI Engineer, you will be at the forefront of developing and delivering innovative GenAI and Agentic AI solutions that generate actionable business insights and transform key areas within GE HealthCare, including Finance, Commercial, Supply Chain, Quality, Operational Excellence and Lean, and Manufacturing.

We are seeking a highly skilled and motivated AI Engineer to join our dynamic team. You will play a pivotal role in shaping and executing our AI strategy. You’ll collaborate across a unified, cross-functional delivery organization - partnering with experts in data engineering, ML engineering, analytics, and GenAI development - to solve complex business challenges and deliver scalable solutions.

Job Description

Core Responsibilities

• Leading development of AI-driven solutions including but not limited to:
• 1) Designing RAG models, agent workflows, and multi-step reasoning models.
• 2) Unstructured data analysis.
• 3) Integrating ML/GenAI models and LLM orchestration into end-user AI applications.
• 4) Conduct research and stay updated with the latest advancements in AI technologies.
• 5) Translate AI research into business solutions.
• Leading development of AI-driven solutions including but not limited to:
• 1) Designing RAG models, agent workflows, and multi-step reasoning models.
• 2) Unstructured data analysis.
• 3) Integrating ML/GenAI models and LLM orchestration into end-user AI applications.
• 4) Conduct research and stay updated with the latest advancements in AI technologies.
• 5) Translate AI research into business solutions.
• Project Execution: Leading and contributing to AI engineering projects from ideation through implementation, ensuring solutions are robust, scalable, and aligned with organizational priorities.
• Cross-Functional Collaboration: working closely with colleagues in data engineering, ML engineering, data science, analytics, GenAI, and business stakeholders to deliver integrated solutions and drive project success.
• Technical Excellence: applying best practices in data preparation, feature engineering, model selection, validation, and deployment. Participate in code reviews and contribute to technical documentation.
• Continuous Improvement: staying current with advancements in ML, GenAI, and analytics. Proactively identify opportunities to improve existing models and processes.
• Business Impact: translating complex AI engineering concepts into actionable insights for business partners, supporting decision-making and measurable outcomes.
• Mentorship & Learning: sharing knowledge with peers, contribute to team learning, and seek opportunities for professional growth.

Requirements

• Experience: Bachelor’s, Master’s or PhD degree in Computer Science, AI, Data Science, Engineering, Applied Mathematics, or related field with direct AI/ML experience in industry with demonstrated success building and deploying enterprise-grade solutions at scale.
• Relevant Expertise: Proven ability to apply AI to solve real-world problems in areas such as forecasting, pricing, customer analytics, sales planning, computer vision, and operational optimization
• Technical Skills: Expertise in the latest AI tools and platforms such as MCP, A2A, AWS Bedrock, Azure AI Foundry, LLM foundational models, and agentic orchestration & monitoring platforms such as LangGraph/LangSmith.
• Expertise in GenAI model development, AI Agent design and orchestration, Computer Vision, Deep Learning, Transformers, Self-Supervised Learning, and LLM fine tuning.
• Industry Knowledge: Understanding of analytics practices relevant to commercial operations, logistics, inventory management, manufacturing, and finance.
• Communication Skills: Strong ability to convey complex technical concepts to non-technical stakeholders and senior executives.
• Interpersonal Skills: Proven success working in cross-functional, hybrid, and virtual teams.
• Ethics & Integrity: Commitment to ethical data science practices.
• Travel: Willingness to travel for business meetings as needed.
• Relocation Assistance Provided: Yes
• Communication Skills: Strong ability to convey complex technical concepts to non-technical stakeholders and senior executives.
• Interpersonal Skills: Proven success working in cross-functional, hybrid, and virtual teams.
• Ethics & Integrity: Commitment to ethical data science practices.
• Travel: Willingness to travel for business meetings as needed.
• Relocation Assistance Provided: Yes

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