Principal AI Software Engineer

Overview

Lead AI-native application architecture and technical strategy for enterprise systems

Key Responsibilities

• ai architecture
• due diligence
• model evaluation
• monitoring
• incident response
• llm integration

Tasks

-Contribute as a thought leader within the team, and help to refine current state as well as future state plans and product roadmaps -Lead technical due diligence and integration planning for major AI technology decisions -Lead investigation and proof-of-concept development for emerging AI technologies and methodologies -Design and architect enterprise-scale full stack applications with sophisticated AI integrations across natural language processing, computer vision, and predictive analytics -Drive adoption of emerging AI technologies and evaluate their strategic impact on product development -Establish monitoring, observability, and cost management frameworks for AI systems across the organization -Establish technical standards, design patterns, and best practices for AI-augmented development across the organization -Drive technical decision-making for complex systems that span multiple teams and products -Manage risk and uncertainty for self and team within a dynamic priority-setting environment -Contribute to open source projects and represent the company at technical conferences and industry events -Act as an enabler for successful execution of identified projects -Define and drive technical vision and architecture for AI-native applications across multiple product areas -Make decisions with confidence when problems or solutions are not well defined -Champion engineering best practices including comprehensive testing, code quality, security, and scalability standards -Lead the development of complex, multi-tenant AI systems serving millions of users with high availability and performance requirements -Lead cross-functional technical initiatives, collaborating with engineering leadership, product management, and data science teams -Lead incident response and post-mortem processes for complex AI system issues -Collaborate with external partners, vendors, and research institutions on cutting-edge AI initiatives -Establish frameworks for AI model evaluation, A/B testing, and performance optimization at enterprise scale -Drive technical innovation initiatives that differentiate our AI capabilities in the market -Establish and maintain technical documentation, architectural decision records, and knowledge sharing practices -Design cost-efficient, scalable LLM integration strategies across multiple providers with advanced optimization and failover mechanisms

Requirements

• cloud
• llm
• python
• react
• phd
• agile

What You Bring

-Must be willing to work out of an office located in Niskayuna, NY. -Experience with technical strategy development and technology roadmap planning -Expert in Agile Development -18+ years of full software development lifecycle experience, including architecture design, technical leadership, and large-scale system optimization -Master’s Degree in Electrical, Computer Science, Computer Engineering, Robotics or related field -Expert-level experience with cloud platforms (AWS, GCP, or Azure) and advanced containerization (EKS), orchestration, and infrastructure as code (GitOps) -Deep expertise with multiple LLM providers and advanced AI orchestration frameworks (LangChain, LlamaIndex, custom frameworks) -Strong background in system design, scalability, and performance optimization for high-traffic applications -Track record of building and scaling AI-powered features for 10M+ users with high availability requirements -Expert-level experience with vector databases (Pinecone, Weaviate, pgvector) and advanced embedding model optimization -12+ years of programming using JavaScript/TypeScript and multiple backend languages (Python preferred, Node.js, Java, or Go) -Advanced expertise in prompt engineering, model optimization, and deep understanding of AI system limitations and capabilities -Extensive experience leading technical teams, driving cross-team initiatives, and providing technical mentorship -Architect advanced RAG (Retrieval-Augmented Generation) systems, agentic workflows, and autonomous AI architectures -Expert knowledge of AI observability tools, cost optimization strategies, and performance monitoring at enterprise scale -Background in machine learning research, AI safety, or advanced AI system design -Must be 18 years or older. -Proven track record designing and shipping complex production applications that incorporate LLMs or AI services at enterprise scale (1M+ users) -Advanced understanding of enterprise RAG architectures, semantic search optimization, and conversation memory management at massive scale -Extensive experience with agent architectures, autonomous AI systems, and cutting-edge agentic workflow implementations -Experience with multi-modal AI integration, model fine-tuning, and deployment of custom AI models -6+ years of experience with modern front-end frameworks (React, Vue, or Angular) and advanced state management patterns -Demonstrated experience with agentic workflows and autonomous AI system architectures -10+ years of non-internship professional software development experience -Legal authorization to work in the U.S. is required. We will not sponsor individuals at the Bachelor’s level for employment visas, now or in the future, for this job opening. -Master's degree or PhD in computer science, AI/ML, or equivalent advanced technical education

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About Ge Vernova

-Traces roots back to Edison and Alstom, merging power, renewable, digital & financial wings. -Headquartered in Cambridge, MA, crafts large-scale gas turbines, SMRs, wind turbines, hydro and grid tech to fuel economies. -On the nuclear front, advancing small modular reactors (like BWRX‑300) in partnership with utilities and supporting semiconductor projects. -Wind prowess spans onshore, offshore and blade making—with key sites like Dogger Bank offshore and blade plants in Spain. -Electrification arm tackles grid stability: HVDC, transformers, storage, conversion, plus GridOS software powering smarter infrastructure. -Weaves finance and consulting through energy-infrastructure investments, funding solar farms to pipelines via GE Energy Financial Services.

Sector Specialisms

Visa Sponsorship

-no visa sponsorship; must have legal u.s. work authorization.

Security Clearance

-offer contingent on successful drug screening.