Prompt Engineer and Data Analyst

Key Responsibilities

• Prompt Engineering & Model Evaluation
• Design, test, and iteratively refine complex and creative prompts to enhance AI model capabilities in reasoning, instruction following, and contextual understanding.
• Conduct rigorous side-by-side (SxS) comparisons of AI-generated outputs, providing detailed rationales and quality ratings to identify the superior response.
• Develop"golden" datasets, ideal responses, and granular evaluation rubrics to serve as benchmarks for model training and performance analysis.
• Engineeradversarial prompts and red-team scenarios to systematically identify model vulnerabilities, biases, and safety gaps across various policies (e.g., Harassment, Hate Speech, Dangerous Content).
• Data Curation & Analysis
• Create, annotate, and review diverse datasets across text, audio, and video formats to support model training and localization.
• Perform in-depth fact-checking and analysis to ensure model responses are accurate, relevant, and grounded in reliable sources.
• Establish and document style guides, content standards, and evaluation procedures to ensure consistency and quality across all projects.
• Analyze model outputs to identify trends, document error patterns, and categorize failures, providing actionable feedback to engineering teams.
• Collaboration & Training
• Train, mentor, and guide other team members on prompt engineering best practices, evaluation methodologies, and quality standards.
• Collaborate with engineering and product teams to translate evaluation insights into actionable model improvements.
• Multimodal AI Training
• For voice projects, script and perform dialogues portraying various personas (e.g., customer, agent) and accents to generate realistic conversational data for AI voice agents.
• For video projects, author precise text prompts using professional video production terminology (e.g., shot angles, camera movements, lighting) to guide generative video models.

Qualifications

• Bachelor's degree or equivalent experience in Linguistics, Computational Linguistics, Communications, Technical Writing, or a related analytical field.
• Native or near-native fluency in English with exceptional writing and editorial skills.
• Proven experience in a role involving AI data annotation, content quality review, search quality rating, or prompt engineering.
• A highly detail-oriented and analytical mindset, with the ability to deconstruct complex instructions and evaluate outputs with precision.
• Ability to interpret code, datasets, and system workflows at a conceptual level (no coding required).
• Ability to work independently and manage workflows effectively in a remote environment.

Nice to Have

• Multilingual proficiency in one or more languages in addition to English.
• Direct experience with generative AI tools for text, voice, or video.
• Background in QA testing, rubric design, or AI safety and ethics evaluation.
• Familiarity with data annotation platforms and model evaluation tools.