Staff AI Engineer — Generative Prompting & LLM Frameworks

LS3002 GE Vernova Operations LLC; Town of Niskayuna (NY); On-site; USD 98,400 - 164,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401(k) matching

Health Coach

Job summary

GE Vernova is building a dedicated AI team to leverage Generative AI and redefine how we engage with our industry. The AI Engineer will create and optimize prompts for LLMs, collaborating with domain experts to deliver software solutions that address internal and external needs.

You will work with developers to integrate LLM capabilities into applications, contribute to a scalable prompt engineering framework, and document processes to support knowledge sharing across business units.

Qualifications

• Bachelor’s degree in CS/Engineering/Math with 5+ years of relevant experience.
• Master’s degree preferred in AI or related field.
• Experience with prompt engineering and AI tooling (GPT, Hugging Face).
• Proficiency in Python and ML libraries (PyTorch, Pandas, NumPy).

Responsibilities

• Create and optimize prompts for a variety of LLM use cases.
• Test, refine, and validate prompts for high accuracy and relevance.
• Collaborate with software developers to integrate LLM solutions into applications.
• Contribute to a scalable framework for prompt engineering and knowledge sharing across units.
• Gather user feedback to continually improve prompt effectiveness.
• Stay up-to-date with advances in LLM technology and document best practices.

Skills

Prompt engineering

LLM integration

Python

PyTorch

Pandas/NumPy

Git

NLP

Communication

Education

Bachelor’s degree in CS/Engineering/Math

Master’s degree preferred

Tools

GPT models

Hugging Face

Job description

GE Vernova is building a dedicated AI team to leverage Generative AI and redefine how we engage with our industry. The AI Engineer will create and optimize prompts for LLMs, collaborating with domain experts to deliver software solutions that address internal and external needs.

You will work with developers to integrate LLM capabilities into applications, contribute to a scalable prompt engineering framework, and document processes to support knowledge sharing across business units.