How to Build a Custom Candidate Search Engine with Real-Time APIs

Recruiting has always been a game of timing and precision. The faster you find the right person, the better your chances of connecting before someone else does. But most sourcing tools fail at the one thing that matters most: accurate, real-time data.

You end up reaching out to candidates who changed jobs months ago, don’t match your filters, or simply aren’t relevant anymore.

If you want to build a system that gives you live, laser-targeted results not stale profiles you need your own candidate search engine powered by real-time APIs.

In this post, we’ll walk through what a modern search engine should look like and how to build your own from scratch.

What is a Candidate Search Engine

A candidate search engine is a system that helps you quickly find people who match your hiring needs. You can search based on job titles, skills, locations, past companies, or even public signals like GitHub contributions.

Unlike static databases that update every few months, a modern candidate search engine works in real time. If a software engineer changes their LinkedIn title today, you can see it today. If someone starts a new project or moves to a new city, you can track that right away.

For recruiting teams, AI recruiters, and builders of sourcing platforms, this speed matters. The faster you find a candidate who matches your criteria, the better your chances of reaching them before other recruiters do.

What a Modern Candidate Search Engine Should Do

A modern recruiting tool should do more than just pull names from a database. It should have the ability to help you find the best fit candidates for your organization at the right time, with all the details you need to take action immediately. Here are the features that make it work.

Real-Time Data

Candidate data should be fresh, not months old. Your search engine should:

• Update profiles daily, not quarterly

• Detect job changes the moment they are posted on LinkedIn or other public sources

• Spot new projects or portfolio additions, such as a recent GitHub repo or Behance upload

• Track location moves, like when a candidate relocates to your target city

Real-time indexing means you are always reaching out based on the most current information.

For instance, a software engineer in Austin, Texas, updates their profile with “Senior React Developer at Stealth Startup.” With real-time indexing, you can see the change today and start outreach before other recruiters even notice.

Flexible Search Logic

Not all great candidates will have a perfect job title match. That’s why you need filters that can dig deeper. Look for:

• Skills and technologies (such as Python, React, Kubernetes)

• Recency of professional activity

• Portfolio or GitHub usage

• Company size and industry

• Location, or preferred locations

Your engine should support multiple filters and combinations so you can refine your candidate search. 

Flexible search logic ensures you find candidates who match both your current needs and your future pipeline requirements.

Example search: Find mid-senior sales managers in B2B SaaS companies (201–1,000 employees), located in New York.

Contact & Context Enrichment

Finding the right candidate is just the first step of the recruitment process. You also need to know if they are worth reaching out to. Therefore, a modern engine should also instantly show:

• Past roles and notable achievements

• Side projects, open-source contributions, or speaking engagements

• Public signals, such as recent LinkedIn posts or GitHub commits

• Contact information (email, phone, if available)

This context saves time researching a candidate using multiple other sources and helps you personalize outreach.

Filter by Geography

Most recruiting teams do not need a global search. Instead, they prefer to narrow results by location. Therefore, a modern search engine should:

• Filter by exact location or radius

• Deliver hyper-relevant lists like “New York-based data engineers with Python experience” instead of “everyone worldwide”

This ensures that you can focus only on candidates who are realistically available for your role.

Incorporate Portfolio and Social Signals

Resumes and public databases give recruiters good knowledge of a candidate. Adding social media activity can help recruiters understand their candidate’s interests and personality better. 

• Surface activity like GitHub, Dribbble, or LinkedIn posts to spot candidates who are active and engaged.

Why Off-the-Shelf Tools Don’t Cut It

Traditional recruiting tools can be a quick starting point, but they often fall short when you need fresh, precise, and flexible data. Most of them update profiles only every few months, so you may be reaching out to candidates who have already changed jobs or are no longer looking.

Search options are often limited to basic “title contains” filters, making it hard to combine skills, location, and activity signals for more accurate results. Many also lack built-in enrichment, forcing you to jump between platforms to get contact details or access detailed information of the company candidates worked at earlier.

If your hiring focus is regional, you might still have to pay for global databases, adding noise and wasted cost.

For recruiting teams that need speed and control, these gaps make a custom, real-time candidate search engine a better choice for them.

For founders building modern recruiting platforms or AI recruiters, a real-time candidate search engine provides an advantage over the legacy recruiting platforms that exist now.

Step-by-Step Guide: Build the Engine

Building a custom candidate search engine with real-time APIs is easier than it sounds. Here’s a simple workflow to get started.

Step 1: Define Your Filters and Query Logic

The first thing to get right is what you’re actually looking for. A job title alone won’t cut it. You’ll want to combine multiple signals like seniority, skills, geography, industry etc, to avoid irrelevant results.

Once you’ve nailed down the candidate criteria, you translate them into a JSON payload for the Search API. This is where filters like title, skills, company_size, or region come into play. Your JSON is just the structured version of your recruiter wishlist.

Decide which filters you need. For example, if you’re looking for recent graduates from Stanford who studied Masters in AI/ML and experience at FAANG companies, the filters you’d need are

• Education Institute Name

• Education degree name

• Education field of study

• Education end date

• Employer Name

• Years of experience

Step 2: Query the Real-Time People API

Next, use the API to pull candidate profiles that match your filters. 

Structure your filters into a JSON payload for the Search API.

Step 3: Enrich Each Result in Real-Time

Once you have the list of candidate names and LinkedIn URLs, pull deeper profile data:

• Contact details - email, phone

• Social links

• Full job role history

• Portfolio links

• Resume text

• Company firmographics

• confidence scores

• Public activity signals
  
  

If you find a high potential candidate who is currently unavailable, you can also set up webhooks to get alerts when a candidate has left their job or posts about leaving their job. 

Step 4: Rank or Score Candidates 

Once you’ve pulled and enriched your candidate list, not every result will be equally strong. Some people check every box. Others? Not so much. This is where candidate scoring helps.

You can create a simple formula that ranks candidates based on how well they match your must-haves. The score doesn’t need to be fancy, it just needs to reflect what matters most to your team.

For example, your scoring system might prioritize:

• Role match (e.g. do their title, skills, and seniority align?)

• Experience signal (years of experience, company pedigree, relevant industries)

• Activity or visibility (GitHub commits, portfolio updates, public talks)

• Recency (how recently they changed jobs or added new skills)

Here’s a rough example:

score = (role_match * 0.4) + (experience_score * 0.3) + (activity_signal * 0.2) + (recency_boost * 0.1)

You don’t need to overengineer it. Even a basic scoring model will help surface your best candidates faster and save your recruiters hours of scrolling.

Once ranked, you can:

• Sort and export your top candidates

• Push the top X into your CRM or ATS

• Or trigger outreach directly via automation

Think of this step as the bridge between sourcing and action. It’s what turns a good candidate list into a promising

When You Should Build Your Own Search Engine

A custom candidate search engine makes sense when your hiring needs go beyond what off-the-shelf tools can handle. If you require real-time data, highly specific filters, and the ability to control enrichment and ranking, building your own system gives you the flexibility and accuracy you need.

It is especially worth considering if:

• You focus on niche roles or emerging skill sets

• You hire across specific geographies and want geo-based pricing or limits

• You need to integrate search directly into your platform, ATS, or internal tools

• You want to own your workflow without depending on third-party platforms

• You need an API-first layer that lets your users build watchlists, track candidates, or run searches inside your own UIHidden Costs and Daily Challenges

Why CrustData is a Fit

CrustData provides everything you need to build and run your search engine in one API. You get:

• Real-time people search with 60+ search filters, nesting and and/or logic that allows for unlimited filter combinations

• Instant enrichment for contact info, job history, skills, and public activity

• Geo-specific targeting to focus on relevant markets

• Webhooks to detect changes like job moves or new projects

• Scoring flexibility so you can rank candidates your way

Instead of stitching together multiple data sources, CrustData gives you a single, reliable feed for sourcing top talent before anyone else reaches them.

Conclusion

Whether you're a recruiter building an internal tool or a founder launching a new product, building your own candidate search engine gives you full control over filters, enrichment, ranking, and results. But to make it work, it needs to be powered by real-time data and accurate, up-to-date people profiles.

That’s where CrustData comes in. We give you one API with everything you need - real-time people search, deep people and company enrichment, so you don’t have to stitch together multiple tools to find the best candidate for you.