This project centers on building an internal tool for a recruitment consultancy that automates the hiring process without manual intervention. You will join a build-first, learn-on-the-job engagement where full context, tool access, and daily guidance are provided by the founder. The work combines automation, structured outputs, a feedback-driven refinement loop, and a simple front-end, with an emphasis on delivering documented workflows ready for handover. The role is targeted at final year students or recent graduates who already have hands-on experience with automation tools and AI APIs.
Project goals and core concept
What the project aims to achieve
The primary aim is to replace manual steps in hiring with an automated system that handles recruitment end-to-end. This includes generating candidate shortlists, accepting HR feedback, refining results, and producing structured outputs, all through automated flows. The emphasis is on creating repeatable, maintainable workflows that remove manual intervention from the hiring lifecycle.
The tool automates the process of hiring – all without manual intervention.
Key themes you will work within
Expect to focus on integration, structured data, feedback-driven refinement, user-facing simplicity, and clear documentation for handover. Each theme maps directly to a deliverable: an integration within your automation environment, JSON outputs for interoperability, a feedback loop to refine shortlists, a minimal front-end to interact with the system, and documentation that captures workflows for future teams.
- Integration with chosen automation tooling.
- Structured output to standardize downstream consumption.
- Feedback loop to iterate and refine candidate selection.
- User interface that is intentionally simple.
- Documentation for clear handover.
Deliverables explained: what you will build
The set of deliverables
You will deliver a set of tangible assets that implement the automated hiring flow. These include an integration for automation tooling, structured JSON output to represent candidate shortlists and related data, a feedback-driven workflow that triggers refinements, a simple front-end for interactions, and documentation of all workflows for handover.
The deliverables are explicitly defined so that the implementation can be evaluated against the expected outputs. Each deliverable complements the others: the integration powers the automation, the JSON output standardizes data, the feedback loop improves selection, the front-end allows users to interact with results, and the documentation ensures continuity after delivery.
How the deliverables relate to one another
- The n8n integration acts as the automation backbone to run flows without manual steps.
- Structured JSON output provides a clear, machine-readable representation of shortlists and related metadata.
- The feedback loop workflow accepts HR input and re-triggers the refinement process to produce a refined shortlist.
- The simple front-end offers a lightweight interface for HR or stakeholders to view results and provide feedback.
- Basic documentation captures all workflows to enable handover to future operators or teams.
Designing the feedback loop and refinement workflow
Purpose of the feedback loop
A central part of the project is a feedback loop where HR feedback triggers a refinement process to improve candidate shortlists. This loop ensures that human evaluation is incorporated into an automated system, enabling the system to produce a refined shortlist based on HR input. The design intent is to couple automated generation with human judgment in a repeatable workflow.
Workflow flow and responsibilities
In this implementation, the workflow accepts HR feedback and uses that input as a signal to re-run the refinement process. The refinements result in an updated shortlist that is output in the structured JSON format. The workflow should be designed to capture feedback reliably and to re-trigger the refinement step whenever new feedback arrives.
The feedback loop should be observable and auditable: HR feedback entries, trigger events, and refined shortlists need to be recorded so that the team can inspect how feedback affects outcomes. The final documented workflow will describe the trigger conditions, inputs, outputs, and any transformations that occur during refinement.
Candidate profile, onboarding, and support
Who should apply
This opportunity is aimed at final year BCA, B.Tech, or BBA-IT students, and at recent graduates who already have hands-on experience with automation tools and AI APIs. The role is explicitly build-first and learn-on-the-job, offering a practical environment to implement the deliverables while gaining real experience.
Onboarding and daily support
You will be provided with full project context, access to the necessary tools, and daily guidance from the founder. The engagement is structured to let you build while you learn, with the founder available to provide direction and feedback throughout the build process. This support model aims to help candidates translate their hands-on experience into deliverables that meet the project requirements.
Expectations during the build
The emphasis is on producing working artifacts: an integration, structured outputs, a functioning feedback loop, a simple interface, and documentation. Because the role is build-first, candidates should be prepared to apply their existing automation and AI API experience directly to produce the deliverables, while using the provided guidance to refine their approach.
Front-end, documentation, and handover
Simple front-end expectations
The front-end requirement is described as simple: it should enable users to view shortlists and submit HR feedback that re-triggers the refinement workflow. Its purpose is to provide a practical interaction point for stakeholders, not to be a feature-rich application. The focus is on usability and clarity so that HR feedback can be captured and passed into the automated flows reliably.
Documentation for handover
Basic documentation of all workflows is required to ensure a smooth handover. Documentation should cover the created workflows, how the integration operates, the structure of JSON outputs, how the feedback loop is triggered, and how to operate the simple front-end. The goal of documentation is to make it straightforward for another person or team to understand and operate the system after delivery.
Documentation acts as the bridge between the delivered artifacts and future maintenance. It should be clear, concise, and focused on the operational aspects of the system so that the recruitment consultancy can pick up, run, and iterate on the tool with minimal friction.
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Getting started and useful resources
How to begin
Begin by familiarizing yourself with the project scope, the required deliverables, and the available tool access provided by the team. Because this is a build-first role, start implementing the pieces in parallel where possible: set up the integration, define JSON schemas, sketch the feedback loop, and create a minimal front-end for HR interaction.
Learning resources and related opportunities
Several internal resources and opportunities are available that may complement your skill set or future pursuits. These include tutorials on AI tools, web design, visual design, and time management, along with listings for other programs and internships that can broaden your experience.
- Free ChatGPT tutorial for practical AI tool skills.
- Free Web Design tutorial for front-end fundamentals.
- Free Canva tutorial for visual assets.
- Free Time Management tutorial to structure your build process.
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Frequently Asked Questions
What is the main objective of the project?
The main objective is to build an internal tool for a recruitment consultancy that automates the process of hiring without manual intervention. The project focuses on delivering an automated flow that handles shortlist generation, incorporates HR feedback, and produces structured outputs ready for use.
What are the concrete deliverables I must produce?
Deliverables include a n8n integration, structured JSON output, a feedback loop workflow where HR feedback re-triggers Gemini to produce a refined shortlist, a simple front-end, and basic documentation of all workflows for handover. Each deliverable is intended to work together to automate hiring end-to-end.
Who is the intended applicant for this role?
The role is intended for final year BCA, B.Tech, or BBA-IT students and recent graduates who have hands-on experience with automation tools and AI APIs. It is a build-first, learn-on-the-job opportunity for individuals ready to apply practical skills while receiving guidance.
What kind of support will I receive during the project?
You will be provided with full context, tool access, and daily guidance from the founder. The engagement is structured so you can build and learn simultaneously, with the founder available to provide direction and feedback throughout the development process.
What is expected in the project documentation and handover?
Basic documentation should describe all workflows, the integration, the structure of the JSON outputs, the feedback loop mechanics, and how to use the simple front-end. The documentation must enable a smooth handover so that future operators can understand and run the system after delivery.
Conclusion
This project offers a focused opportunity to build a practical automation system for recruitment that removes manual intervention from hiring processes. The deliverables are concrete and complementary: an integration, structured outputs, a feedback-driven refinement loop, a simple front-end, and documentation for handover. Candidates with hands-on automation and AI API experience will find a build-first environment with daily founder guidance and tool access, enabling them to learn while producing tangible, operational artifacts.
