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Data Prompt Engineer at NTT DATA
Guadalajara, jalisco, Mexico -
Full Time

Start Date

Immediate

Expiry Date

09 Jan, 26

Salary

0.0

Posted On

11 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Performance Analysis, Data-Driven Improvements, Prompt Engineering, Large Language Model, Technical Knowledge, Python, Analytical Skills, Creativity, Problem-Solving

Industry

IT Services and IT Consulting

Description
Performance Analysis and Improvement: Analyze AI system outputs and user feedback to identify patterns and areas for improvement, implementing data-driven refinements to prompts and context systems. Develop and maintain prompt libraries or repositories for reuse and knowledge sharing across the organization. Overall 5+ years of experience Bachelor's degree in computer science, Linguistics, Computational Linguistics, AI, Machine Learning, Data Science, or a related field, or equivalent experience. LLM Expertise: Deep understanding of Large Language Model (LLM) capabilities, limitations, and optimal interaction patterns, including familiarity with different LLM architectures and prompting techniques. Prompt Engineering Expertise: Advanced proficiency in crafting, testing, and refining prompts to produce consistent, accurate, and appropriate AI outputs. Technical Understanding: Sufficient technical knowledge to collaborate effectively with AI engineers and operations specialists on prompt implementation, optimization, and troubleshooting. Programming Skills: Proficiency in Python is highly beneficial, as it is widely used in AI development and for scripting, automation, and interacting with AI models. Analytical Skills: Strong analytical capabilities to evaluate prompt performance data, identify patterns in AI responses, and implement data-driven improvements. Creativity and Problem-Solving: Ability to think creatively
Responsibilities
Analyze AI system outputs and user feedback to identify patterns and areas for improvement. Develop and maintain prompt libraries or repositories for reuse and knowledge sharing across the organization.