What is a JD and Why Does It Matter?

Job Description (JD) is a crucial document in any recruitment process. It's not just a simple list of requirements that companies put together—it's actually the vital bridge between real hiring needs and finding the right candidates.

A complete JD typically includes information about the position, job responsibilities, required skills and expertise, work experience, and benefits.

Who Writes the JD?

This question seems simple but actually has a significant impact on the quality of the JD. In practice, JDs are usually written by people with deep expertise who truly understand what the job requires.

For IT positions, especially developers, the JD is typically written by the Tech Lead or Engineering Manager. These are the people who understand the technology, know which tech stack is needed, what skill level is required, and what kind of real-world experience will meet the project's demands.

For management positions, the JD is drafted by the direct manager of that role. They have a clear understanding of the leadership capabilities, people management skills, and strategic thinking that the position requires.

The common thread here is that JDs are always written by people with deep expertise in that field—they understand the work inside and out, know what's essential versus what's a bonus, and most importantly, they know what kind of candidate will succeed in that role.

The Silent Struggles of HR

However, once the JD is written, it gets passed to the HR or Talent Acquisition team to search for and screen candidates. And this is where the real challenges begin.

The Expertise Gap

HR professionals are experts in people, recruitment processes, and company culture—but they're not technical experts in every field the company is hiring for. Their knowledge of specialized fields is usually at a general level, understanding basic concepts but not deep enough to accurately assess a candidate's fit.

This creates a significant gap between what's written in the JD and the ability to identify suitable candidates among hundreds, even thousands, of CVs every day.

The Keyword Matching Problem

Identifying keywords in CVs to match with the JD becomes a major challenge. Let's look at some real-world examples:

Case 1: Embedding Engineer Position

When recruiting for an Embedding Engineer position, the JD typically requires C++ skills and hardware knowledge. However, many excellent candidates in this field don't explicitly list these keywords on their CVs. Instead, they might describe projects related to "optimizing embedded system performance" or "developing drivers for IoT devices." HR needs to infer that these experiences require C++ skills and hardware knowledge—which isn't easy and creates gaps that can lead to missing quality candidates.

Case 2: JavaScript Frameworks

Another typical example is when recruiting for a VueJS Developer position. In reality, a developer who's excellent with React or Angular can quickly master VueJS because all three frameworks share many similar concepts and approaches. However, if you're only doing rigid keyword matching, these potential candidates get eliminated right in the first round.

Case 3: Domain Experience

Consider recruiting for a high-traffic system. A candidate with extensive experience building and operating large Ecommerce platforms definitely has the ability to handle issues related to scale, performance, and reliability. But if the JD only emphasizes "high-traffic system" without mentioning Ecommerce, and HR doesn't recognize this connection, an excellent candidate might get overlooked.

Humans Can't Be Experts in Everything

And here's the obvious truth: HR/TA professionals are human too—they can't be experts in every field. You can't expect one HR person to deeply understand AI/ML, master DevOps, be knowledgeable about UI/UX design, know about embedded systems, and understand blockchain all at once. Each of these fields has hundreds of technologies, frameworks, and best practices of its own.

The 100% Matching Trap

Another issue many HR professionals face is the tendency to try matching all requirements in the JD when screening candidates. In reality, though, only some requirements in a JD truly need to be prioritized, while the rest can be flexible or are just nice-to-haves.

This leads to HR tending to eliminate candidates who don't meet 100% of the requirements, while Tech Leads or Hiring Managers usually only need candidates to meet about 60-70% of the core requirements to work effectively and learn the rest on the job.

This gap between HR's expectations (100% matching) and the technical team's actual expectations (60-70% matching of important requirements) causes many good candidates to be missed, leaving both the recruitment team and technical team feeling frustrated.

Knoot JD System - The Solution to Recruitment Challenges

Facing these challenges, Knoot JD System was created as a smart solution to bridge the gap between technical expertise and the recruitment process.

Automatic Analysis and Information Extraction

The system uses advanced AI/LLM technology to automatically analyze the JD and extract important information. It doesn't just stop at identifying skill requirements—the system also categorizes them into groups:

• Must-have requirements: Essential requirements that can't be skipped
• Nice-to-have requirements: Additional skills that are bonuses but not mandatory
• Time and location information: Remote/onsite, fulltime/part-time, project timeline
• Soft skill requirements: Teamwork, communication, logical thinking

Weighted Requirements System

This is the breakthrough feature of Knoot JD System. Instead of treating all requirements equally, the system creates a weighted mechanism for each requirement based on:

• The importance level of the requirement for the job
• How frequently it appears and how it's emphasized in the JD
• Whether the skill can be substituted or learned
• Real experience from similar positions

For example, for a Senior Backend Engineer position working on microservices, the system might weight requirements like this:

• Experience with distributed systems: 25% (must-have)
• Knowledge of Java or Go: 25% (must-have)
• Understanding of Docker and Kubernetes: 15% (important)
• Experience with AWS/GCP: 15% (nice-to-have)
• Knowledge of GraphQL: 10% (bonus)

HR Stays in Control

An important point is that Knoot JD System doesn't completely replace human judgment. HR still has full authority to:

• Adjust the weight of requirements based on feedback from the Hiring Manager
• Add or remove criteria depending on the actual situation
• Override the system's decisions when necessary

Automation with Next-Gen AI

The entire process is powered by advanced AI/LLM models, which help:

• Perform deep semantic analysis, not just simple keyword matching
• Recognize equivalent skills (React ≈ VueJS ≈ Angular)
• Understand context and domain knowledge (Ecommerce experience → High-traffic system)

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