About Job/Role

The Prompt Engineer optimizes prompts to generative AI models across NiCE's Illuminate applications.
Works as part of the Illuminate Research team with multiple business groups to enhance application quality and customer experience.
Partners with global development teams to diagnose and resolve prompt-based issues and define tests for LLM-based systems that are difficult to evaluate with traditional test automation tools.
Educates development teams on advances in prompt engineering and updates production prompts to evolving industry best practices.

Roles and Responsibilities

Regularly review production metrics and problem cases to identify opportunities for improvement.
Diagnose and resolve issues with production prompts in English.
Refine prompts generative AI systems to achieve customer goals.
Collect and present quantitative analysis on solution success.
Work with application developers to implement new production monitoring tools and metrics.
Collaborate with architects and Product Managers to implement prompts supporting new features.
Meet regularly with teams working in United States Mountain and Pacific time zones (UTC-7:00 and UTC-8:00).
Review new prompts and prompt changes with Machine Learning Engineers.
Consult with Machine Learning Engineers for more challenging problems.
Stay informed about new advances in prompt engineering.

Required Qualification

Fluent in written and spoken English.
BS in a technology-related field such as Computer Science, Business Intelligence/Analytics, or Finance.
2-4 years of work experience in a technology-related industry or position.
Familiarity with best practices in prompt engineering, including 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).

Experience

2-4 years in technology-related roles, preferably with exposure to AI/ML or prompt engineering.

Skills

Python programming.
Web app frameworks (Streamlit, Flask).
Familiarity with generative AI application frameworks (LangChain, LlamaIndex, griptape).
Basic AWS resource management, including microservice deployment (preferred).
Containerization via Docker (preferred).
Experience with standard and AI-based testing frameworks such as PyTest and DeepEval (preferred).

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