About the role
As a SQL Engineer, you will work remotely on an hourly paid basis to review AI-generated SQL queries, database designs, and data-processing logic, as well as generate high-quality reference solutions and explanations for complex data problems. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in methodology, query structure, indexing strategy, or conceptual understanding; fact-check data-related claims; write clear, step-by-step explanations and model solutions that demonstrate correct methods; and rate and compare multiple AI responses based on correctness, performance, and reasoning quality. This is a fully remote, hourly paid contractor role with SME Careers, a fast-growing AI data services company and subsidiary of SuperAnnotate that provides AI training data to many of the world’s largest AI companies and foundation model labs. Your SQL and database engineering expertise will directly contribute to improving the world’s premier AI models used across industries. Important There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network. Key Responsibilities Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects. Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance. Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases. Your Profile Bachelor’s degree or higher in Computer Science, Information Systems, Engineering, Mathematics, or a closely related technical field. 7+ years of professional experience working with SQL in production environments as a Database Engineer, SQL Developer, Data Engineer, or similar role. Expert-level proficiency in SQL, including complex joins, window functions, aggregation strategies, and query plan analysis. Demonstrated experience with database performance tuning, indexing strategies, and troubleshooting concurrency or locking issues. Hands-on experience designing relational data models, schemas, and data warehouse structures (star and snowflake schemas). Strong experience with ETL/ELT processes and tooling, as well as working with large-scale data in modern cloud or on-prem data platforms. Minimum C1 English proficiency (written and spoken), with the ability to write clear technical explanations and follow detailed English-language guidelines. Comfort with version control, CI/CD practices, and collaborative workflows for managing database changes. Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus. Highly detail-oriented and systematic, with a methodical approach to evaluating reasoning quality and identifying subtle data or query issues.