Prompt Engineer (Remote, 146 Openings - August 2026)

This Glassdoor aggregated listing features 146 open Prompt Engineer positions as of August 2026, all available for remote work across global locations. In these roles, you will build and maintain the production layer of organizational AI practices, developing, testing, and iterating on production-grade prompts, prompt chains, and LLM-driven components to power internal tools, customer-facing AI products, and automated workflows. Typical responsibilities include collaborating with cross-functional teams of machine learning engineers, product managers, and software developers to align prompt performance with business and user experience goals, conducting rigorous red-teaming and testing to reduce hallucinations and improve output consistency, and documenting scalable prompt workflows for team use. Roles span entry-level to senior experience levels, and are offered by a diverse set of employers across tech, healthcare, finance, e-commerce, and education industries. All positions offer competitive compensation aligned with market rates for AI roles, with many including benefits such as flexible scheduling, professional development stipends for AI certifications, and remote work allowances. To apply, click through to view individual job descriptions, specific requirements, and employer details directly on Glassdoor.

• 1+ year of experience designing, testing, and optimizing prompts for large language models (LLMs) including GPT, Claude, Llama, or other open-source models
• Strong foundational understanding of natural language processing (NLP) concepts, LLM architecture, tokenization, and context window limitations
• Familiarity with prompt engineering best practices including few-shot learning, chain-of-thought prompting, and retrieval-augmented generation (RAG) workflows
• Basic proficiency in Python or similar scripting languages for prompt automation, testing, and integration with LLM APIs
• Excellent written communication and critical thinking skills to craft clear, contextually relevant prompts for targeted domain use cases
• Ability to analyze LLM output performance, identify failure modes and edge cases, and iterate on prompt designs to improve accuracy and relevance
• Experience working in cross-functional agile teams, with strong collaboration, documentation, and problem-solving skills
• Bachelor’s degree in Computer Science, Linguistics, Data Science, or related field, or equivalent practical prompt engineering experience
• Portfolio of published prompt engineering work, open-source contributions, or documented case studies of successful LLM deployments (preferred for senior and lead roles)