AI & LLM Engineer

Job Description Summary

The AI & LLM Engineer will drive the strategy, design, and deployment of advanced Artificial Intelligence and Large Language Model (LLM) solutions to transform engineering, operational processes, and project execution. This role ensures secure, scalable, and compliant AI adoption within power automation workflows, enabling productivity gains, continuous learning, and long-term competitiveness in the utility sector.

Job Description

Roles and Responsibilities

• Lead AI/LLM strategy, solution architecture, and implementation across Engineering, Operations, and Project Delivery.
• Build and maintain LLM-based agents to support:
  • intelligent processing of technical documentation,
  • automated design validation and engineering workflows,
  • testing and QA automation,
  • knowledge retrieval and contextual reasoning.
• Integrate AI into core power automation workflows:
  • IEC 61850 SCD engineering files, relay settings, SCADA HMI & logic, substation documentation, etc.
• Establish AI governance, secure data pipelines, and compliance with utility-grade cybersecurity standards.
• Partner with engineering managers and subject-matter experts to identify high-value AI automation opportunities.
• Develop scalable pipelines for inference, fine-tuning, continuous learning, and lifecycle management in cloud and on-prem environments.
• Evaluate and incorporate emerging AI technologies (RAG, vector stores, autonomous agents, internal copilots).
• Monitor model performance, accuracy, drift, and cost; lead improvement cycles and risk mitigation.
• Train and coach engineering teams on practical AI tools and adoption in daily workflows.
• Ensure compliance with GE Vernova global standards, regulatory expectations, and utility-sector requirements.

Required Qualifications

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, Software Engineering, or related technical field.

• Professional Experience
  • Hands-on experience with AI/ML development and production deployment.
  • Proven track record in full product lifecycle: ideation, prototyping, development, operations.
  • Industrial, energy, or automation domain experience strongly preferred.

Desired Characteristics

Deep expertise with:

• Large Language Models, generative AI, and intelligent agents
• Engineering workflow automation
• Python and modern ML frameworks (e.g., PyTorch, TensorFlow)
• API-driven solution design and MLOps practices
• Cloud infrastructure (AWS, Azure, GCP) and on-prem architectures
• Data governance and cybersecurity best practices

Additional Information