Principal AI Software Engineer

GE Vernova

Niskayuna, United States

Full Time

Posted August 21, 2026

$145k - $145k

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 4, 2026
Classification: Modern power-system classification not yet published for this listing.Legacy source industry field: Power Generation
Pay provenance: Employer-provided pay

Job Description

As a Principal AI Software Engineer, you will drive technical vision and architect enterprise AI applications for multiple initiatives across the company.

Key Responsibilities

Set AI architecture and technical vision across products.
Lead cross-team initiatives with product and data science.
Design RAG and agent workflows; optimize LLM integrations.
Build multi-tenant, high-availability systems with observability.
Establish AI cost management, monitoring, and security standards.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, or related technical field.
10+ years of programming experience in a relevant language using modern front-end frameworks (React, Vue, or Angular) and multiple backend languages (Python preferred, Java, Node.js or Go).
Proven track record designing and shipping production applications that incorporate LLMs or AI services at scale.
Experience with vector databases (e.g. Milvus, Pinecone, Weaviate, pgvector) and advanced embedding model optimization in production applications.
Expertise with multiple LLM providers and advanced AI orchestration frameworks (LangChain, LlamaIndex, custom frameworks).
Extensive experience leading technical teams, driving cross-team initiatives, and providing technical mentorship.
Expert-level experience with cloud platforms (AWS, GCP, or Azure) and advanced containerization (EKS).
13+ years of full software development lifecycle experience, including architecture design, technical leadership, and large-scale system optimization.
Advanced understanding of enterprise RAG architectures, semantic search optimization, and conversation memory management at massive scale.
Experience with multi-modal AI integration, model fine-tuning, and deployment of custom AI models.
Experience with AI observability tools, cost optimization strategies, and performance monitoring at enterprise scale.
Experience with cross-organizational collaboration and influencing other teams’ directions and road maps.
Experience with technical strategy development and technology roadmap planning.
GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).