AI & LLM Engineering Lead
Job Summary
Responsible for departmental operations planning/execution or is focused on execution of professional activities within a technical discipline. Functions with some autonomy but guided by established policies or review of end results.
The job allows modification of procedures and practices covering work as long as the end results meet standards of acceptability (quality volume timeliness etc.).
Essential 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.
Bachelors or Masters degree in Electrical Engineering Computer Science Software Engineering or related technical field.
hands-on experience with AI/ML development and production deployment.
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
Fluent English required
Spanish proficiency preferred
Hands-on experience with RAG pipelines vector databases (FAISS Milvus etc.) and knowledge-graph integrations.
Familiarity with electrical system standards and engineering tools (IEC 61850 SCADA protection & control).
Experience with CI/CD for ML model versioning and observability.
Certifications in AI cloud architecture or cybersecurity.
Demonstrated leadership in digital transformation initiatives.
Relocation Assistance Provided: No
Required Experience:
IC
About Company
GE Vernova's Asset Performance Management software can help you increase asset reliability, minimize costs and reduce operational risks. View a demo today.