(k)®
Local time:
RoleDrop.
/2025/
Technology
React, NodeJS, MongoDB, AWS
Timeline
4 months
Date of launch
Jan 13, 2026
AI Driven Job Platform helping graduates discover, track and manage early-career opportunities.
Role Drop is a web-based platform designed to help students and early-career graduates discover graduate schemes and internships in a clearer, more structured way. The product focuses on personalised job discovery and application tracking, solving a problem the client has seen repeatedly throughout graduate space.The first version of Role Drop has now been fully designed and delivered, laying strong foundations for future growth and iteration. The Challenge Graduates face an overwhelming and fragmented job search process. Opportunities are spread across multiple job boards, company sites, and niche platforms. Often with inconsistent information, unclear deadlines, and no easy way to track progress. From early research, a few clear issues emerged: Job discovery felt generic rather than personalised. Application tracking was manual, messy, or non-existent. Graduates struggled to compare opportunities and stay organised. Existing platforms prioritised listings over user experience. And one clear challenge that we faced was speed, other platforms were competing to supply candidates with roles quickly. RoleDrop wanted to pull roles from multiple platforms and send them to their candidates instantly.
Role Drop is a web-based platform designed to help students and early-career graduates discover graduate schemes and internships in a clearer, more structured way. The product focuses on personalised job discovery and application tracking, solving a problem the client has seen repeatedly throughout graduate space.The first version of Role Drop has now been fully designed and delivered, laying strong foundations for future growth and iteration. The Challenge Graduates face an overwhelming and fragmented job search process. Opportunities are spread across multiple job boards, company sites, and niche platforms. Often with inconsistent information, unclear deadlines, and no easy way to track progress. From early research, a few clear issues emerged: Job discovery felt generic rather than personalised. Application tracking was manual, messy, or non-existent. Graduates struggled to compare opportunities and stay organised. Existing platforms prioritised listings over user experience. And one clear challenge that we faced was speed, other platforms were competing to supply candidates with roles quickly. RoleDrop wanted to pull roles from multiple platforms and send them to their candidates instantly.
/Our Role/
Members of our team acted as the Product Owner and Technical Lead, responsible for the project end-to-end.
Members of our team acted as the Product Owner and Technical Lead, responsible for the project end-to-end.
This involvement included: - Product discovery and concept definition - Requirement gathering and MVP scoping - UX and user flow Design - Feature prioritisation and roadmap planning - Technical architecture planning - Sprint planning and management - Testing and feedback iterations - Project managing developers throughout delivery - Version 2 scoping The first version of RoleDrop was successfully delivered, providing: - A complete end-to-end user journey - Personalised job discovery - In-depth AI job scraping architecture, allowing the platform to retrieve roles from multiple platforms, bringing them into RoleDrop and pushing them to users based on their personal preferences. - A functional application tracking system - A scalable foundation for future features The product is now well-polished for further development, including smarter recommendations, richer analytics and expanded opportunity coverage. Version 2 requirements scoping is currently undergoing.
This involvement included: - Product discovery and concept definition - Requirement gathering and MVP scoping - UX and user flow Design - Feature prioritisation and roadmap planning - Technical architecture planning - Sprint planning and management - Testing and feedback iterations - Project managing developers throughout delivery - Version 2 scoping The first version of RoleDrop was successfully delivered, providing: - A complete end-to-end user journey - Personalised job discovery - In-depth AI job scraping architecture, allowing the platform to retrieve roles from multiple platforms, bringing them into RoleDrop and pushing them to users based on their personal preferences. - A functional application tracking system - A scalable foundation for future features The product is now well-polished for further development, including smarter recommendations, richer analytics and expanded opportunity coverage. Version 2 requirements scoping is currently undergoing.
/Processes/
The team work meticulously throughout each key phase of the project from discovery and planning to technical delivery.
The team work meticulously throughout each key phase of the project from discovery and planning to technical delivery.
Discovery & Planning I began by defining the core user problem and mapping the graduate journey, from discovering opportunities to tracking applications over time. This informed the initial MVP scope and helped keep the product focused on real user needs rather than feature bloat. Key activities included: - Defining target personas - Mapping end-to-end user journeys - Prioritising features for a realistic MVP - Writing structure product requirements Wire-framing & UX Designs My UX designs focused heavily on clarity and simplicity. The goal was to make the platform feel calm and supportive, not overwhelming and clunky. Key UX considerations: - A personalised onboarding flow to understand user preferences - A clean job discovery experience with filtering and ranking - An application tracking dashboard that felt intuitive and lightweight - Clear information hierarchy to reduce cognitive load Wireframes and flows were designed to be easily extensible as new features were to be introduced in future versions. Technical Architecture & Delivery From a technical perspective, the product was designed with scalability in mind. So it was imperative to choose to correct architecture. Decisions included: - Structuring job data in a normalised, flexible format. - Designing the system to support multiple data sources (scraping + APIs) - Planning and accommodating AI-driven recommendation logic - Ensuring the architecture could evolve without major rewrites I worked closely with the development team throughout implementation, ensuring product intent and UX decisions were preserved during the build.
Discovery & Planning I began by defining the core user problem and mapping the graduate journey, from discovering opportunities to tracking applications over time. This informed the initial MVP scope and helped keep the product focused on real user needs rather than feature bloat. Key activities included: - Defining target personas - Mapping end-to-end user journeys - Prioritising features for a realistic MVP - Writing structure product requirements Wire-framing & UX Designs My UX designs focused heavily on clarity and simplicity. The goal was to make the platform feel calm and supportive, not overwhelming and clunky. Key UX considerations: - A personalised onboarding flow to understand user preferences - A clean job discovery experience with filtering and ranking - An application tracking dashboard that felt intuitive and lightweight - Clear information hierarchy to reduce cognitive load Wireframes and flows were designed to be easily extensible as new features were to be introduced in future versions. Technical Architecture & Delivery From a technical perspective, the product was designed with scalability in mind. So it was imperative to choose to correct architecture. Decisions included: - Structuring job data in a normalised, flexible format. - Designing the system to support multiple data sources (scraping + APIs) - Planning and accommodating AI-driven recommendation logic - Ensuring the architecture could evolve without major rewrites I worked closely with the development team throughout implementation, ensuring product intent and UX decisions were preserved during the build.
Discovery
UX Design
Software
MVP
/More projects.
Year
Project name
Description
4.9 / 5
We’ve helped 95+ businesses
hit their targets—yours could be next.
4.9 / 5
We’ve helped 95+ businesses
hit their targets—yours could be next.
klickit®
/Stay in the loop.
Our updates and insights straight into your inbox
klickit®
/Stay in the loop.
Our updates and insights straight into your inbox
klickit®
/Stay in the loop.
Our updates and insights straight into your inbox
klickit®
/Stay in the loop.
Our updates and insights straight into your inbox