GE Vernova AI Agentic Engineering Intern - Summer 2026

As a GE Vernova accelerator, GE Vernova Advanced Research is driving strategy and leading research & development efforts to execute on the business’s mission to help power the energy transition. We forge the collaborations and help invent the technologies required to electrify and decarbonize for a zero-carbon future.

Representing virtually every major scientific and engineering discipline, our researchers are collaborating with GE Vernova’s businesses, the U.S. government, and more than 420 entities at the forefront of technology to execute on 150+ energy focused projects. Collectively, these research programs and initiatives aim to solve near term technical challenges, deliver next generation product advances, and drive long term breakthrough innovation to enable more affordable, reliable, sustainable, and secure energy.

Come and join our powerful, unified force with the energy to change the world. Our mission is BIG.

Our TRANSFORMATION is key – bringing the right businesses together to LEAD the ENERGY TRANSITION. Our TEAM is ready.

Addressing the climate crisis is an urgent global priority and we take our responsibility seriously. Building on over 130 years of experience tackling the world’s challenges, GE Vernova is uniquely positioned to help lead the energy transition by continuing to electrify the world while simultaneously working to decarbonize it. GE Vernova helps customers power economies and deliver electricity that is vital to health, safety, security, and improved quality of life.

GE Vernova is seeking a highly skilled AI Agent Engineering Intern to design, develop, and deploy advanced autonomous AI agents leveraging LLMs and advanced AI/ML techniques. The ideal candidate will build intelligent Agents capable of perceiving, reasoning, and acting within complex digital or real-world environments, integrating AI models into scalable applications that solve real-world business challenges autonomously.

What You'll Do:

• Design, implement, and optimize AI Agents using LLMs, reinforcement learning, planning algorithms, and decision-making frameworks.
• Develop scalable multi AI Agent architectures supporting long horizon reasoning, autonomy, planning, interaction, and complex task completion.
• Integrate AI Agents with APIs, backend services, databases, and enterprise applications.
• Prototype, deploy, and maintain AI-driven systems ensuring reliability and performance in production environments.
• Optimize agent behavior through continuous feedback, reinforcement learning, and user interaction.
• Collaborate closely with research, engineering, product, and deployment teams to iterate on agent capabilities and innovate continuously.
• Monitor AI Agent performance, conduct rigorous evaluations, implement safety guardrails, and ensure ethical AI practices.
• Document AI Agent architectures, design decisions, workflows, and maintain comprehensive technical documentation.
• Stay current with emerging AI technologies, contribute to platform and tooling improvements, and share knowledge within the team.
• Your mission is to push the boundaries of planning, reasoning, and agentic intelligence. You will design and implement large-scale AI/ML solutions integrating the latest state of the art research in our global products

What You'll Bring (Basic Qualifications):

• Working towards a Masters Degree in a technical field of Artificial Intelligence, Machine Learning, AI Engineering.
• Minimum 4.0 GPA out of 5.0 scale (without rounding)
• Applicants must be currently authorized to work in the United States without the need for employer sponsorship. This role is not eligible for employer immigration sponsorship, now or in the future.
• Must be willing to work out of an office located in Niskayuna, NY.

What Will Make You Stand Out:

• Proficiency in Python and/or languages like JavaScript, TypeScript, Node.js, or Java, Go, with strong coding and software engineering practices.
• Expertise with AI/ML libraries and frameworks such as LangChain, OpenAI APIs, PyTorch, TensorFlow, commercial or open source LLMs.
• Hands-on experience with LLMs, prompt engineering, and natural language processing (NLP).
• Knowledge of agent orchestration platforms and multi-agent systems (e.g., AutogenAI, LangGraph, MCP protocol).
• Familiarity with data management, vector databases, semantic retrieval, and real-time data pipelines.
• Experience deploying AI systems on cloud platforms (AWS, Google Cloud) with container orchestration (Docker, Kubernetes).
• Strong understanding of machine learning model training, fine-tuning, and evaluation techniques.
• Awareness of AI ethics, data privacy, and secure handling of sensitive information.