AI & LLM Engineer

Job Description Summary

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

Relocation Assistance Provided: Yes