AI & LLM Engineer

GE Vernova

Noida, India

Full Time

Posted October 13, 2026

Power Generation

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Listing evidence and provenance

Source: Workday View original listing
Freshness: Open in the current public read path; this is not an employer guarantee.Last observed October 14, 2026
Classification: Modern power-system classification not yet published for this listing.Legacy source industry field: Power Generation
Pay provenance: Pay not available

Job Description

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.

Key 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.

Requirements

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.