Prompt Engineer and Data Analyst

Welo Data works with technology companies to provide datasets that are high-quality, ethically sourced, relevant, diverse, and scalable to supercharge their AI models. As a Welocalize brand, WeloData leverages over 25 years of experience in partnering with the world’s most innovative companies and brings together a curated global community of over 500,000 AI training and domain experts to offer services that span:

ANNOTATION & LABELLING: Transcription, summarization, image and video classification and labeling.

ENHANCING LLMs: Prompt engineering, SFT, RLHF, red teaming and adversarial model training, model output ranking.

DATA COLLECTION & GENERATION: From institutional languages to remote field audio collection.

RELEVANCE & INTENT: Culturally nuanced and aware, ranking, relevance, and evaluation to train models for search, ads, and LLM output.

Want to join our Welo Data team? We bring practical, applied AI expertise to projects. We have both strong academic experience and a deep working knowledge of state-of-the-art AI tools, frameworks, and best practices. Help us elevate our clients' Data at Welo Data.

Are you passionate about the nuances of language and shaping the future of artificial intelligence? Welo Data is seeking a creative and analytical Prompt Engineer & Data Analyst to join our team. In this role, you will be instrumental in refining and evaluating large language models (LLMs). You'll design prompts, create high-quality datasets, and perform rigorous analysis to directly improve the functionality, accuracy, and safety of cutting-edge AI systems. Your expertise will help us build smarter, more reliable, and more helpful technology.

• 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.
• Engineer adversarial 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.

• 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.

• 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.