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Open nowPosted yesterday

Sr Principal AI Software Engineer

GE Vernova1,741 open roles

Where
Remote
Work mode
Remote
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Your applicationOpen nowSr Principal AI Software EngineerGE Vernova · Remote

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The clock on this job

Early applications get read.

8.1% of postings close within 7 days. Measured by our own scanner across the market. GE Vernova postings stay open a median of 29 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.5%3 days
  3. 8.1%7 days
  4. 15.1%14 days
  5. 33.9%30 days
This job: posted yesterday

GE Vernova median: 29 days open

The posting

Job Description Summary

As 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

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

Additional Information

Relocation Assistance Provided: Yes

#LI-Remote - This is a remote position

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