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Lead enterprise AI architecture, strategy, and technical vision across products and business segments. Design and deploy scalable GenAI applications using LLMs, agent workflows, RAG, vector databases, NLP, and computer vision. Establish standards for AI security, monitoring, cost management, responsible AI, and documentation. Partner with product, data science, engineering, executives, customers, and vendors while mentoring teams and driving reusable AI platforms and services.
Job Description SummaryAs a Senior Principal AI Software Engineer, you will establish a technical vision, oversee and lead AI architecture, AI platform and identify reusable foundational services to accelerate AI application development. Using your AI expertise, competitive intelligence and customer knowledge to conceive, evaluate, and design Industrial AI Service offerings.
Apply a strategic understanding of the timing and rationale of AI design choices and help decide upon critical design areas early in the development process. You’ll drive new ways of thinking, across groups within business units, to improve quality, engineering productivity and responsiveness to feedback and changing priorities.
You’ll integrate LLMs, agent workflows, NLP, computer vision, RAG, and predictive analytics to build secure, high-availability and cost efficient AI based solutions.
We will count on you to tailor communication to a variety of audiences and perspectives and anticipate issues to prevent conflict. We will depend on you to choose appropriate internal or external technologies, incorporate research, and create designs that are reused across teams. We’ll count on you being an excellent judge of AI practices that work well.
You’ll partner with product, data science, engineering leaders, business executives, and CIOs. You’ll mentor teams, and raise standards in AI development, testing, security, and documentation. We support growth, autonomy, and collaboration across research and product.Job Description
#LI-Remote - This is a remote position
Apply a strategic understanding of the timing and rationale of AI design choices and help decide upon critical design areas early in the development process. You’ll drive new ways of thinking, across groups within business units, to improve quality, engineering productivity and responsiveness to feedback and changing priorities.
You’ll integrate LLMs, agent workflows, NLP, computer vision, RAG, and predictive analytics to build secure, high-availability and cost efficient AI based solutions.
We will count on you to tailor communication to a variety of audiences and perspectives and anticipate issues to prevent conflict. We will depend on you to choose appropriate internal or external technologies, incorporate research, and create designs that are reused across teams. We’ll count on you being an excellent judge of AI practices that work well.
You’ll partner with product, data science, engineering leaders, business executives, and CIOs. You’ll mentor teams, and raise standards in AI development, testing, security, and documentation. We support growth, autonomy, and collaboration across research and product.Job Description
Responsibilities
- Influence AI strategy, direction and policy.
- Oversee and lead all AI architecture and technical vision across products and solutions.
- Lead cross-team initiatives with product and data science.
- Lead architecture and support implementation on large scale AI program across business segments
- Design agent workflows, RAG architecture and develop approaches to develop custom LLMs with specific domain data.
- Represent GE Vernova as a subject-matter-expert with partners, vendors and customers.
- Apply your knowledge of AI trends to develop new practices.
- Review business requirements and help the team understand trade offs.
- Establish AI cost management, monitoring, and security standards.
REQUIRED QUALIFICATIONS
- Bachelor’s degree in Computer Science, Computer Engineering, or related technical field
- Extensively demonstrated programming experience in a relevant language using modern languages (Python preferred, Java, Node.js or Go)
- Proven experience designing and deploying production GenAI applications that use large language models at scale.
- Experience with vector databases (e.g. pgvector, Milvus, Pinecone) and advanced embedding model optimisation in production applications
- Expertise with multiple LLM providers, advanced AI orchestration frameworks (LangChain, LlamaIndex, custom frameworks), Eval frameworks and creating custom agents.
- Extensive experience leading technical teams, creating technical strategy, and providing technical mentorship
- Expert-level experience with cloud platforms (i.e AWS, GCP, or Azure) and advanced containerisation (EKS)
- Familiarity with best practices for responsible AI, including data privacy, bias mitigation, and model monitoring.
- Systematic problem-solving approach, strong communication skills, a sense of ownership and drive.
PREFERRED QUALIFICATIONS
- Extensively demonstrated experience of full software development lifecycle experience, including architecture design, technical leadership, and large-scale system optimization
- Advanced understanding of enterprise RAG architectures, semantic search optimisation, 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 optimisation strategies for different AI application types, and performance monitoring at enterprise scale
- Experience with cross-organisational collaboration and communicating technology strategy across a variety of stakeholders.
- Experience with technical strategy development and technology roadmap planning
Relocation Assistance Provided: Yes
GE Vernova Bellevue, Washington, USA Office
Bellevue, United States, 0
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
