CareerCompass — Job Search App

Overview

CareerCompass is a job-search app for mobile that we designed and built as a product. It helps people find relevant vacancies quickly by combining a strong filter panel with search shortcuts and saved searches. Its audience is job seekers who check for openings repeatedly, often between other activities on their phones.

The Challenge

Job hunting produces an overload of results. A broad search returns more listings than anyone can read, while a narrow one risks missing good fits. On a small screen the problem sharpens: there is little space for controls, and every extra tap costs attention. Job seekers also repeat the same searches over and over, so rebuilding a query each visit wastes time. The product needed to make precise searching fast and to remember what the user cared about.

Who Uses It and How

A graduate opens a popular-search shortcut for entry-level roles and browses. An experienced professional builds a detailed filter combination, saves it and returns each morning to see what is new. Employers or a listings operator supply job data, and an administrator manages the listing feed, removes expired or duplicate postings and checks that logos and company names appear correctly.

Our Approach

We put filtering at the centre. A capable filter panel narrows results along the dimensions that matter to each user, so the list on screen already reflects their needs. For speed we added popular-search shortcuts for roles people frequently look for, giving new users an instant way in without typing, and for return visits, saved searches turn a complicated query into a single tap. Company logos on results let candidates scan a list by employer at a glance. Search quality drove the choice of Elasticsearch, with a Node.js API between it and a React Native app.

What We Built

The main search screen offers a filter panel that supports detailed queries, with results updating accordingly. Popular-search shortcuts sit near the top for the most common roles. Each result shows the company logo alongside the role details, keeping the list easy to scan. Users can save a search with one tap and return to it later, and the saved queries reflect the same filters the user selected.

Architecture and Data

Job listings are indexed in Elasticsearch, with fields for title, description, company, location and other filterable values. The Node.js service receives requests from the app, builds the query, applies filters, ranks results by relevance and returns a page at a time. Filters such as location or contract type map to exact-match conditions, while text search uses analysed fields so variations of a word still match. A saved search is stored as the set of query and filter values, which can be re-run on demand.

Security, Privacy and Quality

The app collects little beyond account details and the searches a user saves, but search history can reveal someone's employment plans, so it should be private to the user and never visible to employers. Elasticsearch should not be exposed directly to the internet; the API sits in front, validating input and limiting requests. We tested relevance with typical queries and misspellings, checked filter combinations that return no results and verified performance on long result lists.

Technology

Elasticsearch is designed for full-text search with filters and relevance ranking, which is exactly what a job board needs and something a general-purpose database handles poorly at scale. Node.js suits the API layer between app and index, and React Native lets one codebase serve iOS and Android.

Outcome

CareerCompass gives job seekers a fast route from a broad market to the listings that fit them. Precise filters, shortcuts and one-tap saved searches reduce repeated effort, while the search infrastructure is built to handle detailed queries over a large set of listings. The base is ready for further features such as alerts or application tracking.

Frequently asked questions

How much does it cost to build a job search app?

Cost depends on where listings come from (your own postings, employer submissions or third-party feeds), the filters and search relevance needed, user accounts, alerts and employer tools, and platforms. Search infrastructure adds work compared with a simple list. We scope after understanding your data.

Why use Elasticsearch for a job board?

It is built for fast text search combined with filters and ranking, and it copes with large sets of listings, which relational databases usually handle less well. It typically runs alongside a primary database.

What features make a job app useful for returning users?

Saved searches, alerts and quick filters save people from repeating queries. Making the most common actions one tap away matters most on a phone.