Key Takeaways

  • 75% of U.S. employers use automated applicant tracking systems to screen resumes before a human reviews them (Harvard Business School & Accenture, 2021)
  • The most common ATS failures are missing keywords, incompatible formatting, and incorrect file types
  • ResumeGeni scores your resume across 8 parsing layers — modeled on the same steps enterprise ATS platforms like Workday, Greenhouse, and Taleo use to evaluate candidates

How ATS Resume Scoring Works

Applicant tracking systems parse your resume into structured data — extracting your name, contact info, work history, skills, and education — then score how well that data matches the job requirements. Many ATS rejections happen because the parser couldn't extract critical fields, not because the candidate wasn't qualified.

LayerWhat It ChecksWhy It Matters
Document extractionFile format, encoding, readabilityCorrupted or image-only PDFs fail immediately
Layout analysisTables, columns, headers, footersMulti-column layouts break field extraction
Section detectionExperience, education, skills headingsNon-standard headings cause sections to be missed
Field mappingName, email, phone, dates, titlesMissing contact info is a common cause of immediate rejection
Keyword matchingJob-specific terms, skills, certificationsKeyword overlap affects recruiter search visibility and ATS scoring
Chronology checkDate ordering, gap detectionReverse-chronological order is expected by most ATS
QuantificationMetrics, numbers, measurable outcomesQuantified achievements help human reviewers and some scoring models
Confidence scoringOverall parse quality and completenessLow-confidence parses get deprioritized in results

Frequently Asked Questions

Is ResumeGeni free?
Yes. ResumeGeni is currently in beta — ATS analysis, scoring, and initial improvement suggestions are free with no signup required. Full guidance and saved reports may require a free account.
What file formats are supported?
PDF, DOCX, DOC, TXT, RTF, ODT, and Apple Pages. PDF and DOCX are recommended for best ATS compatibility.
How is the ATS score calculated?
Your resume is processed through an 8-layer parsing pipeline that extracts structured data the same way enterprise ATS platforms do. The score reflects how completely and accurately your resume can be parsed, plus how well your content matches common ATS ranking criteria.
Can ATS read PDF resumes?
Yes, but not all PDFs are equal. Text-based PDFs parse well. Image-only PDFs (scanned documents) and PDFs with complex tables or multi-column layouts often fail ATS parsing. Our analyzer will flag these issues.
How do I improve my ATS score?
Focus on three areas: use a clean single-column format, include keywords from the job description naturally in your experience bullets, and ensure all sections (contact, experience, education, skills) use standard headings.

ATS Guides & Resources

Built by engineers with 12 years of experience building enterprise hiring technology at ZipRecruiter. Last updated .

Cybersecurity Engineer

Aisi · London, UK

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About the AI Security Institute

The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We’re in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally.

We’re here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action.

About the Team 

The Cyber and Autonomous Systems Team (CAST) is looking to research and map the evolving frontier of AI capabilities and propensities to inform critical security decisions that reduce loss-of-control risks from frontier AI. We focus on preventing harms from high-impact cybersecurity capabilities and highly capable autonomous AI systems.   

Our team is a blend of high-velocity generalists and technical staff, from organisations such as Meta, Amazon, Palantir, DSTL and Jane Street. Our recent work has included building model evaluations suites – such as Replibench - the world’s most comprehensive evaluation suite for understanding the risk of a model autonomously replicating itself over the internet. We also regularly test the cyber and other relevant capabilities of frontier models, before they are released, to understand their risks. 

As AI systems become more advanced, the potential for misuse of their cyber capabilities may pose a threat to the security of organisations and individuals. Cyber capabilities also form common bottlenecks in scenarios across other AI risk areas such as harmful outcomes from biological and chemical capabilities and from autonomous systems. One approach to better understanding these risks is by conducting robust empirical tests of AI systems so we can better understand how capable they currently are when it comes to performing cyber security tasks. In this role, you'll join a strongly collaborative team to help create new kinds of capability and safety evaluations to evaluate frontier AI systems as they are released. 

About the Role

This is a cybersecurity engineer position focused on building environments and challenges to benchmark the cyber capabilities of AI systems. You'll design cyber ranges, CTF-style tasks, and evaluation infrastructure that allows us to rigorously measure how well frontier AI models perform on real-world cybersecurity tasks. 

This work belongs inside UK government because understanding AI cyber capabilities is critical to national security, and robust empirical testing requires coordination across government, industry, and international partners to inform policy decisions on AI safety. 

You'll work closely with research engineers, infrastructure engineers, and machine learning researchers across AISI. As a small, fast-moving team building first-of-its-kind evaluation infrastructure, you'll be able to influence research directions, own whole pieces of work, and bring your ideas to the table. 

Core Responsibilities 

  • Evaluation Design & Development (60%) 
    • Design cyber ranges and CTF-style challenges for automatically grading AI system performance on cybersecurity tasks
    • Build agentic scaffolding to evaluate frontier models, equipping them with tools such as network packet capture utilities, penetration testing frameworks, and reverse engineering/disassembly tools 
    • Design metrics and interpret results of cyber capability evaluations 
  • Infrastructure engineering (30%) 
    • Work alongside other engineers to ensure evaluation environments are robust and scalable 
  • Research & Communication (10%) 
    • Write reports, research papers and blog posts to share findings with stakeholders 
    • Keep up-to-date with related research taking place in other organisations 
    • Contribute to AISI's broader understanding of AI cyber risks   

Example Projects 

  • Onboard and integrate new cyber ranges into our evaluation pipeline 
  • Conduct agent research to improve the cyber capabilities of our agents 
  • Improve grading and scoring methodologies for automated evaluation tasks 
  • Integrate defensive telemetry and simulated users into ranges to increase their realism 
  • Collaborate with government partners on joint research publications 

Impact 

Your work will directly shape the UK government's understanding of AI cyber capabilities, inform safety standards for frontier AI systems, and contribute to the global effort to develop rigorous evaluation methodologies. The evaluations you build will help determine how advanced AI systems are assessed before deployment

 

What we are looking for

We're flexible on the exact profile and expect successful candidates will meet many (but not necessarily all) of the criteria below. 

Essential 

  • Strong Python skills with experience writing scripts for automation or security tooling 
  • Proven experience in at least one of the following areas of cybersecurity red-teaming: 
    • Penetration testing 
    • Cyber range design 
    • Competing in or designing CTFs 
    • Developing automated security testing tools 
    • Bug bounties, vulnerability research, or exploit discovery and patching 
  • Strong interest in helping improve the safety of AI systems 

Preferred 

  • Familiarity with virtualisation technologies such as Proxmox VE and infrastructure-as-code approaches to enable reproducible test environments to be rapidly spun up for testing 
  • Ability to communicate the outcomes of cybersecurity research to a range of technical and non-technical audiences 
  • Familiarity with cybersecurity tools such as network packet capture utilities, penetration testing frameworks, and reverse engineering/disassembly tools 
  • Active in the cybersecurity community with a track record of keeping up to date with new research 
  • Previous experience building or measuring the impact of automation tools on cyber red-teaming workflows 

Example backgrounds 

  • Penetration tester with 1+ years experience; has designed CTF challenges or cyber ranges; strong Python skills; interested in AI safety 
  • Content engineer at a cybersecurity training platform; experienced in building vulnerable machines, CTF challenges, and automated deployment infrastructure 
  • Security researcher with experience in vulnerability research or bug bounties; familiar with penetration testing frameworks and reverse engineering tools; has communicated findings to mixed audiences 

Core requirements   

  • This is a full time role.   
  • You should be able to join us for at least 24 months.   
  • You should be able work from our office in London (Whitehall) for several days each week, but we provide flexibility for remote work. 
  • We would like candidates to be able to start in Q2 2026  

 

What We Offer 

Impact you couldn't have anywhere else 

  • Incredibly talented, mission-driven and supportive colleagues. 
  • Direct influence on how frontier AI is governed and deployed globally. 
  • Work with the Prime Minister’s AI Advisor and leading AI companies. 
  • Opportunity to shape the first & best-resourced public-interest research team focused on AI security. 

Resources & access 

  • Pre-release access to multiple frontier models and ample compute. 
  • Extensive operational support so you can focus on research and ship quickly. 
  • Work with experts across national security, policy, AI research and adjacent sciences. 

Growth & autonomy 

  • If you’re talented and driven, you’ll own important problems early. 
  • 5 days off learning and development, annual stipends for learning and development and funding for conferences and external collaborations. 
  • Freedom to pursue research bets without product pressure. 
  • Opportunities to publish and collaborate externally. 

Life & family* 

  • Modern central London office (cafes, food court, gym) or option to work in similar government offices in Birmingham, Cardiff, Darlington, Edinburgh, Salford or Bristol. 
  • Hybrid working, flexibility for occasional remote work abroad and stipends for work-from-home equipment. 
  • At least 25 days’ annual leave, 8 public holidays, extra team-wide breaks and 3 days off for volunteering. 
  • Generous paid parental leave (36 weeks of UK statutory leave shared between parents + 3 extra paid weeks + option for additional unpaid time). 
  • On top of your salary, we contribute 28.97% of your base salary to your pension. 
  • Discounts and benefits for cycling to work, donations and retail/gyms. 

*These benefits apply to direct employees. Benefits may differ for individuals joining through other employment arrangements such as secondments. 

 

Salary

Annual salary is benchmarked to role scope and relevant experience. Most offers land between £65,000 and £145,000 made up of a base salary plus a technical allowance (take-home salary = base + technical allowance). An additional 28.97% employer pension contribution is paid on the base salary. 

This role sits outside of the DDaT pay framework given the scope of this role requires in depth technical expertise in frontier AI safety, robustness and advanced AI architectures. 

The full range of salaries are available below: 

  • Level 3: £65,000–£75,000 (Base £35,720 + Technical Allowance £29,280–£39,280) 
  • Level 4: £85,000–£95,000 (Base £42,495 + Technical Allowance £42,505–£52,505) 
  • Level 5: £105,000–£115,000 (Base £55