We are seeking an experience senior python Developer to architect, build, and maintain high-performance backend systems and APIs.
In this role, you will lead technical design decisions, write clean and scalable production code, and mentor junior engineers while collaborating with cross-functional teams to deliver robust software solutions.
Responsibilities
Review, annotate and evaluate AI-generated SQL responses for correctness, clarity, query logic, joins, syntax, performance, security, and readability.
Create detailed prompts and reference solutions to guide AI learning on complex data challenges.
Assess solutions for accuracy, adherence to prompts, and identify errors in methodology, query structure, indexing strategy, or conceptual understanding.
Deliver clear, constructive feedback and detailed technical explanations to support continuous model improvement.
Run and validate proof-of-work code, fact check data-related claims, and rate/compared AI responses based on reasoning quality.
Build automated SQL audit queries that can scan the annotated dataset daily to flag duplicates, conflicting labels, null values, or out of distribution samples before they reach the ML Team.
Partner with ML Engineers to test proposed annotation guidelines against actual database records.
Requirements
7+ years of professional experience working with SQL in production with SQL in production environments as a Database Engineer, SQL Developer, Data Engineer, or similar role.
Bachelors' degree or higher in computer science, information systems, Engineering, mathematics, or a related technical field
Expert-level proficiency in SQL, including complex joins, windows functions, aggregation strategies, query plan analysis, and performance tuning.
Hands-on experience designing relational data models, schemas, and data warehouse structures (star and snowflake schemas).
Exceptional written and spoken English (c1 level or higher) with the ability to write clear technical explanations,
A methodical, systematic approach to evaluating reasoning quality and identifying subtle data or query issues.