NICE Prompt Engineer 

United States, Utah, Sandy 

953885574

When a customer needs to address novel requirements with a custom prompt, the Prompt Engineer partners with customer-facing teams such as Professional Services and Product Management to capture the customer's needs and develop a robust, well-tested prompting solution. This includes devising and executing custom test plans, as well as presenting quantitative test results to internal stakeholders.

RESPONSIBILITIES

* Review production prompts for problems and potential improvements.
* Educate global development teams on state-of-the-art best practices in prompt engineering.
* Help diagnose and resolve issues with production prompts.
* Work with customer-facing stakeholders to capture customers' goals for generative AI applications.
* Refine prompts to generative AI systems to achieve customer goals.
* Build software tools and prototypes to help compare alternative solutions.
* Collect and present quantitative analysis on solution success.
* Consult with Machine Learning Engineers for more challenging problems.

* Help evaluate evolving AI-based tools from other members of the Research team.
* Collect data to refine solutions, models, and analysis frameworks.
* Coordinate with internal domain experts and data labeling teams to build datasets.

* Stay informed about new advances in prompt engineering.

* BS in technology-related field such as computer science, business intelligence/analytics, or finance.
* Three years' work experience in a technology-related industry or position.
* Familiarity with best practices in prompt engineering, to include differences in prompts between major LLM vendors.
* Ability to develop and maintain good working relationships with cross-functional teams.
* Ability to clearly communicate and present to internal and external stakeholders.
* Experience with Python and at least one web app framework for prototyping, e.g., Streamlit or Flask.

* Basic AWS resource management, including microservice deployment.
* Containerization via Docker.
* Awareness of basic data science and generative AI methods.
* Exposure to generative AI application frameworks like LangChain, LlamaIndex, and griptape.