GE Vernova-posted 2 months ago
Full-time • Mid Level
Town of Niskayuna, NY

GE Vernova is seeking a highly skilled AI Agent Engineer 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. 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.

  • 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.
  • Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, AI Engineering, or related fields.
  • Minimum 2-3 years of experience in AI, GenAI application development & deployment particularly with autonomous agent systems or related AI software engineering roles.
  • Demonstrated ability to work independently in fast-paced, experimental environments.
  • Hands-on experience designing and building GenAI apps that allow users to experience AI use cases supporting features like agent orchestration, multi-step reasoning, prompt engineering, RAG integration, and model selection.
  • Expertise with LLMs and deep learning models, machine learning lifecycle management, data generation methods, model training & validation coupled with strong fundamentals and passion in software engineering and system architecture.
  • Legal authorization to work in the U.S. is required.
  • 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.
  • Great work environment
  • Professional development
  • Challenging careers
  • Competitive compensation
  • Relocation Assistance Provided
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