AI Job Search That Matches Roles to Your Resume

How the job search works

You start by describing the job you want in ordinary language, the way you would to a recruiter: the title, the kind of company, whether you want remote or on-site work, and any hard limits such as a minimum salary. InterviewPlan turns that description into structured filters instead of asking you to fill in a dozen dropdowns.

It then reads the profile built from your uploaded resume. That profile holds your skills, the years of experience behind each one, your past titles and the locations you will consider. Every posting is scored against that profile, so the list you see is ordered by fit with you, not by how recently an employer paid to promote it.

Each result shows a match score and the reasons behind it. If a role is a strong match because six of its eight required skills appear in your history, you see that. If it is a weak match because it asks for ten years of experience and you have four, you see that too, before you spend an evening tailoring an application for it.

The profile is editable. If the resume parser read a skill wrongly, or you have experience that never made it onto the page, you can correct it in the Your Details section of your account and every score updates. Changing your preferences invalidates the cached scores, so what you see always reflects what you currently want.

What job matching looks at

A match score that cannot be explained is not useful, so the scoring is built from named parts that you can read. Each part answers a question a recruiter would ask while screening you.

Semantic matching is used as well as keyword overlap, because the same skill is written many ways. A posting that asks for “stakeholder management” and a resume that says “worked with product and sales leads to agree priorities” describe the same experience, and plain keyword matching would miss it.

From a saved job to a prepared interview

Search is the first of four stages in the InterviewPlan ecosystem, and it is designed to hand its results to the next stage instead of ending in a list. Once you save a job, the posting becomes a job description inside your account. That means the same text can drive everything that follows without you copying and pasting it between tools.

• Tailor the resume. The Resume Builder edits your resume against the specific posting, and you accept or reject each suggestion. It only reorders and rewords what is already true of you.
• Apply. The auto-apply stage drafts the resume, cover letter and answers for you to review before anything is sent.
• Prepare for the interview. Mock interviews and the behavioral coach use the same job description, so the questions you practise are the ones this employer is likely to ask.
• Get help in the interview. The interview copilot can draw on the resume and the job description during a live call.
• Settle into the role. After an offer, job support carries on from the first week into the first 90 days.

Because every stage reads from the same resume and the same job description, work you do at the start is not thrown away at the end. Nothing in this chain acts on its own: you choose which jobs to save, which suggestions to accept and which applications to send.

What it covers, and what it does not

It is worth being direct about coverage, because job search tools are often vague about it. InterviewPlan reads postings from employer job boards hosted on applicant tracking systems such as Greenhouse and Lever. It is not a global index of every vacancy on the internet, and it does not scrape sites that forbid it.

That has two consequences. You will see a deep, current list for the companies whose boards are connected, with details such as the full requirements and the stated salary where the employer published one. You will not see every job at every company. For roles outside the connected boards, the sensible route is to add the job description yourself and use the rest of the platform on it.

Coverage grows over time as more employer boards are connected. If a search returns few results, widening the location or work-mode filters usually helps more than rewording the title, because the limiting factor is the set of boards rather than how the query is phrased.

How to get a better search out of it

The quality of the ranking depends on the quality of the profile behind it. A few habits make a noticeable difference to how useful the list is.

• Upload your most complete resume first, then check the skills it extracted. A skill that is missing from the profile cannot count towards a match.
• Describe the role you want, not the role you have. Searching for your current title will keep returning your current job.
• Set a real salary floor. It removes roles you would never accept and makes the remaining scores more meaningful.
• Use the match reasons as a checklist. If the same missing skill keeps appearing in strong-but-not-perfect matches, it is the clearest signal of what to learn or to add to your resume if you already have it.
• Review saved jobs weekly and drop the ones you no longer want, so the list stays a short queue rather than a graveyard.

The best result of a good search is a short list. Twenty well-matched roles that you apply to carefully will do more for you than two hundred that you applied to in bulk, which is a point the guide to how many jobs to apply to per day takes up with data.

Your data and your control

Your resume and preferences are used to rank jobs for you and to prepare your applications. They are not shared with employers until you choose to apply, and no application is sent without your approval. You can edit or remove your profile details at any time.

Matching is a recommendation, not a verdict. A low score does not mean you cannot do a job, and a high score does not mean you will get it. It is a way to spend your limited attention where it is most likely to pay off.

Frequently asked questions