AI career platform
An AI interview practice platform with adaptive questions, résumé-aware RAG, structured feedback and progress analytics.
01 / Project story
Static question lists do not adapt to a candidate's resume, target role or previous performance.
An AI practice platform combines resume-aware retrieval, adaptive questioning and structured feedback with progress tracking.
02 / Product capabilities
Designed as part of a cohesive ai career platform experience, with clarity, reliability and practical use in mind.
Designed as part of a cohesive ai career platform experience, with clarity, reliability and practical use in mind.
Designed as part of a cohesive ai career platform experience, with clarity, reliability and practical use in mind.
Designed as part of a cohesive ai career platform experience, with clarity, reliability and practical use in mind.
03 / Benefits
Personalizes preparation
Makes practice repeatable
Highlights improvement areas
04 / Trade-offs
AI feedback is advisory, not definitive
Resume data requires careful privacy handling
05 / Technology
The architecture for AI Interview Platform was shaped around the product workflow, integration boundaries and long-term maintainability. Technologies are used for specific responsibilities rather than added only to make the stack appear larger.
Supports the AI Interview Platform workflow as a focused part of the product architecture, selected for practical delivery and maintainability.
Provides language understanding and generation for assisted product workflows.
Grounds AI output in retrieved, approved knowledge instead of relying only on model memory.
Stores embeddings and supports semantic retrieval for context-aware AI experiences.
Interface, business logic, persistence and external services remain separated so changes are easier to reason about.
Validation and predictable contracts protect downstream workflows from incomplete or unexpected input.
Runtime limits, secrets, external dependencies and failure paths are considered as part of the implementation.
06 / Delivery approach
Understand the users, business objective and constraints.
Map the core journey and reduce unnecessary interaction.
Implement maintainable interfaces, services and data flows.
Test behavior, responsiveness and failure paths before release.
Project by Sandipan Das