> Markdown version of [/jobs/ext/3767332-principal-ai-software-engineer](https://www.wearedevelopers.com/jobs/ext/3767332-principal-ai-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Principal AI Software Engineer

- **Company:** GE Vernova
- **Location:** United States
- **Experience:** Expert
- **Salary:** $145,400.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Application Integration Architecture, Microsoft Azure, Cloud Computing, Encodings, Computer Engineering, Memory Management, Monitoring of Systems, Python (Programming Language), Machine Learning, Node.Js, Azure Machine Learning, Search Technologies, Software Engineering, Pinecone, ReactJS, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Llamaindex, AgentCore, Vue.js, Pgvector, Containerization, AngularJS, Kubernetes, Information Technology, Performance Monitor, Milvus, Machine Learning Operations, Front End Software Development
- **Published:** October 16, 2026
- **Apply:** https://jobs.military.com/career/367311/principal-ai-software-engineer-new-york-ny-niskayuna

## About the Role

* Bachelor's degree in Computer Science, Computer Engineering, or a related technical discipline.\n
 * Minimum of 10 years of professional software development experience, including mastery of modern front-end frameworks (React, Vue, or Angular) and robust backend languages (Python preferred; Java, Node.js, or Go).\n
 * Demonstrated experience architecting and deploying production-grade applications leveraging LLMs or AI/ML services.\n
 * Strong practical experience with vector databases (e.g., Milvus, Pinecone, pgvector) and embedding model optimization.\n
 * Expertise in AI orchestration frameworks such as LangChain, LlamaIndex, or AgentCore.\n
 * Deep proficiency in cloud-native development (AWS, GCP, or Azure) and containerization (EKS/Kubernetes).\n
 * Proven ability to communicate complex technical strategies to diverse stakeholder groups.\n, * 13+ years of experience across the full software development lifecycle.\n
 * Advanced understanding of large-scale enterprise RAG, semantic search, and conversation memory management.\n
 * Experience with multi-modal AI, model fine-tuning, and the deployment of custom AI models.\n
 * Expertise in AI observability tools, performance monitoring, and rigorous cost-optimization strategies.\n
 * A track record of influencing technology roadmaps and driving cross-organizational collaboration.\n

## Description

* Architectural Leadership: Set the technical vision and architectural standards for AI initiatives, ensuring alignment with organizational goals.\n
 * AI Integration: Lead the design and implementation of RAG architectures, complex agent workflows, and LLM orchestration.\n
 * System Design: Build and maintain multi-tenant, high-availability AI systems with a focus on observability and performance at scale.\n
 * Operational Excellence: Define and enforce standards for AI security, cost management, and model monitoring.\n
 * Mentorship & Collaboration: Lead cross-functional initiatives by partnering with product, data science, and engineering teams to elevate technical standards through mentorship and collaborative design.\n