
Mona Beldi developed advanced AI-driven talent assessment and onboarding features for the Dar-Blockchain/talentai repository, focusing on scalable workflows and robust data models. Over three months, she engineered APIs for generating and analyzing interview, onboarding, and project questions, integrating AI/ML and prompt engineering to automate candidate evaluation. Her work included secure Hedera wallet-based account creation, persistent assessment tracking, and migration to TogetherAI for improved AI scalability. Using JavaScript, Node.js, and Mongoose, Mona enhanced backend reliability, data integrity, and auditability. The solutions streamlined candidate screening, standardized project evaluations, and enabled data-driven decision-making, reflecting a deep understanding of backend and AI integration.

July 2025 highlights for Dar-Blockchain/talentai: Delivered AI-assisted assessment capabilities and analytics to standardize project evaluations and enable data-driven decisions across talent projects. Focused on creating a scalable, user-centered workflow with robust data models and AI prompts.
July 2025 highlights for Dar-Blockchain/talentai: Delivered AI-assisted assessment capabilities and analytics to standardize project evaluations and enable data-driven decisions across talent projects. Focused on creating a scalable, user-centered workflow with robust data models and AI prompts.
June 2025 monthly performance summary for Dar-Blockchain/talentai focusing on onboarding and job assessment systems, data modeling, and API enhancements. The work delivered combines substantial feature improvements, reliability safeguards, and clear business value in talent evaluation, onboarding efficiency, and data-driven decisioning.
June 2025 monthly performance summary for Dar-Blockchain/talentai focusing on onboarding and job assessment systems, data modeling, and API enhancements. The work delivered combines substantial feature improvements, reliability safeguards, and clear business value in talent evaluation, onboarding efficiency, and data-driven decisioning.
May 2025 performance summary for Dar-Blockchain/talentai: Strengthened hiring workflow and on-chain reliability while expanding AI capabilities. Key features delivered include Hedera wallet-based account creation with secure transaction signing, AI Interview Questions Generator API, persistence/linking of job assessments, migration to TogetherAI across AI features, and AI-driven ToDo List for candidate profiles. Major bugs fixed include Gmail signing issues in Hedera integration and robust evaluation result parsing. Impact: faster candidate screening, improved data integrity and auditability, and scalable AI workloads. Technologies demonstrated: Hedera SDK wallet signer pattern, TogetherAI integration, API design, DB persistence, AI toolchains, and robust JSON parsing.
May 2025 performance summary for Dar-Blockchain/talentai: Strengthened hiring workflow and on-chain reliability while expanding AI capabilities. Key features delivered include Hedera wallet-based account creation with secure transaction signing, AI Interview Questions Generator API, persistence/linking of job assessments, migration to TogetherAI across AI features, and AI-driven ToDo List for candidate profiles. Major bugs fixed include Gmail signing issues in Hedera integration and robust evaluation result parsing. Impact: faster candidate screening, improved data integrity and auditability, and scalable AI workloads. Technologies demonstrated: Hedera SDK wallet signer pattern, TogetherAI integration, API design, DB persistence, AI toolchains, and robust JSON parsing.
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