Senior Principal AI Software Engineer

GE Vernova

. Establish technical vision and oversee AI architecture and platforms .

Posted 10/8/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI architecture and platforms, with a strong focus on designing and deploying large-scale GenAI applications. Proven ability to lead technical teams, influence AI strategy, and implement best practices in AI development and security.

Highest-signal resume keywords

AI Architecture LeadershipLarge Language Model DeploymentCloud Platform ExpertiseAdvanced AI Orchestration FrameworksTechnical Team Mentorship

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python ProgrammingGenAI Application DevelopmentEmbedding Model OptimizationVector Database ExperienceAI Cost ManagementCustom AI Model DeploymentRAG Architecture DesignAI Observability ToolsSemantic Search OptimizationModel Fine-Tuning

Soft Skills

Strong Communication SkillsSystematic Problem-SolvingOwnershipDrive

Tools & Technologies

AWSGCPAzureEKSLangChainLlamaIndexPgvectorMilvusPinecone

Industry Keywords

Responsible AI Best PracticesData PrivacyBias MitigationModel MonitoringCross-Organizational CollaborationTechnology StrategyRoadmap Planning

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformJavaJavaScriptNode.jsPythonGo

About the role

Key responsibilities & impact

Establish technical vision and oversee AI architecture and platforms
Identify reusable foundational services to accelerate AI application development
Conceive, evaluate, and design Industrial AI Service offerings
Influence AI strategy, direction, and policy
Lead cross-team initiatives with product and data science teams
Lead architecture and support implementation of large-scale AI programs across business segments
Design agent workflows and RAG architecture
Develop approaches for custom LLMs using domain-specific data
Represent GE Vernova as a subject-matter expert with partners, vendors, and customers
Apply AI trends to develop new practices
Review business requirements and clarify trade-offs
Establish AI cost management, monitoring, and security standards
Partner with product leaders, data scientists, engineering leaders, business executives, and CIOs
Mentor teams and raise standards in AI development, testing, security, and documentation

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Computer Engineering, or related technical field
Extensively demonstrated programming experience in a relevant language; Python preferred, Java, Node.js, or Go
Proven experience designing and deploying production GenAI applications using large language models at scale
Experience with vector databases such as pgvector, Milvus, or Pinecone
Advanced embedding model optimization experience in production applications
Expertise with multiple LLM providers
Experience with advanced AI orchestration frameworks such as LangChain, LlamaIndex, or custom frameworks
Experience with evaluation frameworks and creating custom agents
Extensive experience leading technical teams, creating technical strategy, and providing technical mentorship
Expert-level experience with cloud platforms such as AWS, GCP, or Azure
Advanced containerization experience, including EKS
Familiarity with responsible AI best practices, including data privacy, bias mitigation, and model monitoring
Systematic problem-solving approach, strong communication skills, ownership, and drive
Preferred: full software development lifecycle experience, enterprise RAG architectures, semantic search optimization, conversation memory management, multimodal AI integration, model fine-tuning, custom AI model deployment, AI observability tools, AI cost optimization, performance monitoring, cross-organizational collaboration, technology strategy, and roadmap planning

Benefits

Comp & perks

Relocation assistance provided
Remote work arrangement