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Prompt Engineer at Checkmate. In this hybrid role, you will blend traditional software engineering with natural language processing expertise to develop and maintain systems that leverage LLMs to solve real-world challenges in the restaurant tech domain. You’ll collaborate with cross-functional teams to implement AI-driven features that support everything from customer service automation to order management, reporting, and staff training.. Essential Job Functions:. . . Prompt Development & Optimization. : Design, build, test, and refine prompts for AI tasks like Q&A, classification, extraction, and synthetic data creation.. . . Evaluation & Testing Build . robust test suites using tools like . CoVal, LangFuse, and Galileo. to measure prompt accuracy, compliance, and performance at scale.. . . Performance Analysis & Improvement. : Analyze prompt outputs using metrics, product feedback, and business goals. Iterate to maximize accuracy and reliability.. . . Collaboration:. Work closely with operations, product, data science, and engineering teams to ensure prompts meet quality standards. . . Model Adaptation:. By understanding their unique behaviors, create effective prompts across different models (GPT, LLaMA, Gemini, and internally fine-tuned LLMs).. . . End-to-End Ownership. Drive prompts projects from planning to deployment, including monitoring and continuous improvement.. . . Team Leadership & Mentorship. Lead a team of analysts, guiding their evaluations and data work to support prompt development. Mentor and collaborate with ops teams to ensure seamless integration of prompts into production.. . 100% Remote. Minimum of three years of experience in the areas of AI, ML, NLP, and prompt engineering.. $125,000 to $160,000. Requirements:. . Strong Python programming skills. . Solid data and computer science fundamentals. . Experience with relational databases (e.g., MySQL, PostgreSQL, Oracle, MS SQL). . Hands-on development experience, preferably full-stack. . Good data processing and testing skills. . Ability to handle ambiguous problems and drive projects from start to finish. . Strong problem-solving mindset with a drive to improve and optimize systems. . Ability to use scientific and analytical approaches to measure and evaluate designs. . Excellent communication skills. . Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field. . Flexible to work US hours until at least 6 pm ET with a strong remote setup. . Preferred Qualifications. . Experience with multiple LLMs and tools like LangFuse and Galileo. . Knowledge of cloud platforms (AWS, GCP, Azure, OpenStack) and tools like Docker and Kubernetes. . Focus on scalability, performance, and cost optimization in cloud environments. . Broad technical expertise across front-end and back-end systems. . Familiarity with machine learning concepts and workflows. . Master’s or PhD in Computer Science, Engineering, Math, Physics, or related field. . Company Location: United States.