Ayoub Taoufik

Case 06

AI recruitment workflow platform

A recruitment platform connecting candidate and recruiter workflows, with LLM-assisted profiles and CVs and job listings synced from multiple sources.

Freelance delivery

Freelance full-stack engineer · product delivery

I built candidate and recruiter workflows for a freelance AI recruitment platform, including CV management, matching, application tracking, interview scheduling, and analytics.

The problem
Candidates needed workflows for profiles, CVs, job matches, applications, and interview scheduling. Recruiters needed candidate information and analytics, alongside AI-assisted features and job data from multiple sources.
What I built
I built workflows for CV management, job matching, application tracking, interview scheduling, and analytics. I also integrated LLM-assisted profile and CV capabilities and job-data synchronisation from multiple sources.
What changed
The platform connected candidate and recruiter workflows for CVs, matching, applications, scheduling and analytics, with LLM-assisted profiles and CVs and multi-source job listings. Delivery covered frontend, backend, search and infrastructure.
Fig. 06.1Candidates and recruiters needed connected workflows for profiles, CVs, matching, applications and scheduling, with job data from several sources.Now both sides work in one place and meet on the application and the interview. AI helps with profiles and CVs.

Candidate and recruiter cards sit on either side of a shared application and interview. The candidate card lists a CV with AI help, job matches, and applications; the recruiter card lists shortlists, interview scheduling, and analytics. A small chip notes jobs synced from several sources.

Candidate
CVAI help with your CVLLM-assisted profiles and CVs
Job matches
Applications
ApplicationInterview
e.g. Tue 10:00
Recruiter
ShortlistInterview schedulingAnalytics
Jobs synced from several sourcesUnder the hood: shared workflows · multi-source job-data sync

Candidate and recruiter workflows

Candidates could manage profiles and CVs, review job matches, track applications, and schedule interviews. Recruiters could work with candidate information and analytics.

The platform brought both workflows together, with LLM-assisted profile and CV capabilities and job data from multiple sources.

Product delivery

I built candidate and recruiter workflows for CV management, job matching, application tracking, interview scheduling, and analytics. I integrated LLM-assisted profile and CV capabilities and job-data synchronisation from multiple sources.

The stack included Vue.js, NestJS, TypeScript, the OpenAI API, Elasticsearch, Redis, MongoDB, and Docker.

  1. Candidates

    From profile to application progress

    Candidates could manage CVs, review job matches, track applications, and schedule interviews.

  2. Recruiters

    Candidate information and analytics

    Recruiters could review candidate information and use analytics within the same platform.

  3. AI and data

    Assistance within the workflow

    The platform included LLM-assisted profile and CV capabilities, search components, and job data synced from multiple sources.

Full-stack implementation

I delivered frontend, backend, search, data, and infrastructure work for the recruitment workflows, including LLM-assisted profile and CV capabilities and job data synced from multiple sources.

Scope

What I built

Built

01
  • Candidate profiles and CV management
  • Job matching and application tracking
  • Interview scheduling and analytics

Integrated

02
  • LLM-assisted profile and CV capabilities
  • Multi-source job-data synchronisation

Stack

  • Vue.js
  • NestJS
  • TypeScript
  • OpenAI API
  • Elasticsearch
  • Redis
  • MongoDB
  • Docker