
In April 2025, Mikhail Pivovarov developed three core features for the profcomff/rating-api repository, focusing on auditability, performance, and developer efficiency. He implemented a comment approval workflow with an audit trail, enabling flexible moderation and role-based responses. Enhancements to the rating API introduced multi-criteria sorting and improved retrieval logic, resulting in faster and more accurate listings. Mikhail also integrated AI-assisted code review using Mistral AI, automating code analysis and comment generation. His work leveraged Python, SQL, and SQLAlchemy, demonstrating strong backend development and database modeling skills while aligning technical improvements with business needs for scalable, maintainable review workflows.

April 2025 — Delivered three core features for profcomff/rating-api with a focus on auditability, retrieval performance, and developer efficiency. Implemented Comment Approval Workflow and Auditing, enhanced Rating API sorting/retrieval, and integrated AI-assisted code review with Mistral AI. Stabilized the API through targeted fixes and thorough testing, aligning technical changes with business value (improved moderation control, faster and more accurate listings, and scalable review workflows). Technologies demonstrated include backend API design, migrations, multi-criteria sorting, and AI integration.
April 2025 — Delivered three core features for profcomff/rating-api with a focus on auditability, retrieval performance, and developer efficiency. Implemented Comment Approval Workflow and Auditing, enhanced Rating API sorting/retrieval, and integrated AI-assisted code review with Mistral AI. Stabilized the API through targeted fixes and thorough testing, aligning technical changes with business value (improved moderation control, faster and more accurate listings, and scalable review workflows). Technologies demonstrated include backend API design, migrations, multi-criteria sorting, and AI integration.
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