How to use AI to find jobs you're qualified for

Why keyword matching wastes your time

Standard job board algorithms look for words in common between your resume and a posting. They do not check whether you meet the visa requirement, whether the role is remote or requires relocation, whether the seniority level fits your years of experience, or whether the time zone overlap works for a distributed team.

The result is a feed full of roles you cannot take. You open ten listings, read through each one, and discover that three require sponsorship you cannot get, two are on-site in a city you do not live in, and one is a director role when you have two years of experience. That is time you will not get back, and it compounds across weeks of searching.

• Visa and work authorisation requirements buried in paragraph four
• Location requirements listed as 'hybrid' but meaning three days on-site in a specific city
• Seniority mismatches where 'mid-level' means eight years at that company
• Time zone requirements for async-first teams that exclude certain regions
• Salary ranges that fall below your minimum, disclosed only at the bottom

What eligibility-aware AI actually checks

An eligibility-aware system reads the full text of a posting, not just the title and bullet points. It extracts structured signals: required versus preferred qualifications, location and remote policy, visa sponsorship availability, years of experience, specific tools or certifications, and any explicit exclusions.

It then compares those signals against what you have told it about yourself: your location, your authorisation to work in a given country, your experience level, your skills, and your preferences. The output is a match score that reflects real eligibility, not surface-level keyword overlap.

In practice this means a posting that says 'must be authorised to work in the US, no sponsorship available' is filtered out for a candidate on an open work permit in Canada, even if every other requirement matches perfectly.

1. The AI reads the full posting text, including footnotes and legal disclosures
2. It extracts hard requirements versus nice-to-haves
3. It checks those requirements against your confirmed profile details
4. It assigns a score and explains which factors drove it up or down
5. It surfaces only the roles where you clear the hard requirements

How to build a profile that makes matching accurate

The quality of eligibility matching depends entirely on the accuracy of your profile. Vague inputs produce vague results. If you list your location as 'remote' without specifying your country, the system cannot check visa requirements. If you describe your experience as 'several years', it cannot compare that against a posting that says 'minimum five years required'.

Be precise about the things that create hard eligibility gates. Your country of residence and work authorisation status matter more than your job title. Your actual years of experience in a specific skill matter more than a general summary. Any certifications that are listed as required should be named exactly as they appear on your credential.

Update your profile when your situation changes. If you receive a new visa, move to a different city, or complete a certification, those changes affect which roles you qualify for and should be reflected immediately.

• Country of residence and current work authorisation status
• Exact years of experience per skill or domain, not a range
• Certifications by their official name, for example AWS Certified Solutions Architect Associate
• Whether you are open to relocation and to which cities or countries
• Minimum acceptable salary so roles below it are deprioritised

Reading a match score before you apply

A match score is only useful if you understand what it is measuring. A high score on a keyword-based system means your resume contains similar words to the posting. A high score on an eligibility-aware system means you meet the hard requirements and a meaningful portion of the preferred ones.

When you see a score, look at the breakdown. Which requirements did you meet? Which did you fall short on? A role where you meet every hard requirement but lack two preferred qualifications is a strong candidate for an application. A role where you meet the preferred qualifications but fail a hard requirement is not worth applying to regardless of how good the overall score looks.

Use the score as a triage tool, not a final decision. A score in the mid-range is a prompt to read the posting carefully and decide whether the gap is closeable, for example by taking a short course or framing existing experience differently in your resume.

How Break-In Bad handles eligibility matching

Omar reads the full text of each posting, including location policy, visa sponsorship language, seniority signals, and required tools. She compares those against the details you have confirmed in your profile and scores the role. Roles at 75 or above are applied to automatically on Greenhouse, Lever, Workday, and other employer sites, with a screenshot sent to you as proof. Roles between 45 and 74 are queued for your review so you can decide whether to proceed.

Before any application goes out, Omar writes a tailored resume and cover letter using only facts you have confirmed. She does not invent credentials or rephrase your experience in ways that overstate it. Every line is checked against what you said. You start with 50 free credits on signup, and credits never expire, so there is no pressure to rush through applications.

What to do when you are underqualified for most roles you want

If eligibility-aware matching consistently returns low scores for the roles you are targeting, that is useful information. It tells you there is a real gap between your current profile and the market for those roles, and it tells you specifically what that gap is.

Common gaps include a missing certification that appears as a hard requirement across many postings, a lack of experience with a specific tool that has become standard in your target field, or a seniority level that requires more years than you have. Each of these has a concrete fix.

For certifications, check whether the credential can be earned in under three months. AWS, Google Cloud, and Microsoft Azure all offer associate-level certifications that many candidates complete in six to twelve weeks of part-time study. For tool gaps, look for free tiers or trial accounts that let you build a small project you can reference in applications. For seniority gaps, consider targeting roles one level below your goal to build the track record that justifies the next step.

• Identify the single requirement that appears most often in rejected matches
• Check whether a short course or certification closes that gap
• Build a small project that demonstrates the missing skill
• Target adjacent roles where your current profile scores above 75
• Revisit your target roles after three to six months of deliberate skill building