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 .

Staff / Senior AGI Solutions Engineer

Jazzx Ai · Bangalore, Karnataka

About JazzX AI: 
 
Vision: Enterprises operating on institutional intelligence—governed, self-improving, and scalable beyond individual expertise.

JazzX AI is defining the future of enterprise work—by building AI-native digital workers that actually get the job done.
 
We believe enterprises don't scale expertise—they lose it. Knowledge stays trapped in individuals, judgment gets applied inconsistently, and the best talent spends time on work that should run itself. We're changing that. 

JazzX AI transforms messy enterprise reality into institutional intelligence: governed digital workers that capture expert judgment, make every decision explainable, and continuously improve through real-world execution. The result is faster decisions, higher-quality outcomes, and reliable execution at scale—in domains where getting it wrong isn't an option.
 
We're starting with lending and due-diligence workflows—complex, regulated, high-stakes. From here, we're building the backbone for enterprise intelligence across industries.
 
This is early-stage, hard, and consequential work. If you want to be part of bringing AI systems to market that actually run in production, handle real complexity, and deliver real outcomes—not demos, not chatbots—JazzX AI is the place.

Headquartered in Los Altos, CA. Backed by SAIGroup.
 
About SAIGroup :
 
SAIGroup a private investment firm that has committed $1B to build and scale next-generation, AI-powered enterprise software companies. SAIGroup’s portfolio serves 2,000+ global enterprise customers, generates nearly $800M in annual revenue, and employs 4,000+ people worldwide — providing JazzX AI with long-term capital, deep operating expertise, and access to real-world enterprise scale from day one.

Learn more about JazzX AI:
Website: https://jazzx.ai
LinkedIn: https://www.linkedin.com/company/jazzx-ai

Learn more about SAIGroup:
Website: https://saigroup.ai

 

Job Title: Senior AGI Engineer – GTM Solution Delivery 

Role Overview 

As a Senior AGI Engineer you are the hands-on technical force that turns JazzX’s AGI platform into working, measurable solutions for customers. You will: 

  • Build and integrate LLM-driven features, vector search pipelines, and tool-calling agents into client environments. 
  • Collaborate with solution architects, product, and customer-success teams from discovery through production rollout. 
  • Contribute field learnings back to the core platform, accelerating time-to-value across all deployments. 

You are as comfortable writing production-quality Python as you are debugging Helm charts, and you enjoy explaining your design decisions to both peers and client engineers. 

Key Responsibilities 

Focus Area 

What You’ll Do 

Solution Implementation 

* Develop and extend JazzX AGI services (LLM orchestration, retrieval-augmented generation, agents) within customer stacks. 
* Integrate data sources, APIs, and auth controls; ensure solutions meet security and compliance requirements. 
* Pair with Solution Architects on design reviews; own component-level decisions. 

Delivery Lifecycle 

* Drive proofs-of-concept, pilots, and production rollouts with an agile, test-driven mindset. 
* Create reusable deployment scripts (Terraform, Helm, CI/CD) and operational runbooks. 
* Instrument services for observability (tracing, logging, metrics) and participate in on-call rotations. 

Collaboration & Support 

* Work closely with product and research teams to validate new LLM techniques in real-world workloads. 
* Troubleshoot customer issues, triage bugs, and deliver patches or performance optimisations. 
* Share best practices through code reviews, internal demos, and technical workshops. 

Innovation & Continuous Learning 

* Evaluate emerging frameworks (e.g., LlamaIndex, AutoGen, WASM inferencing) and pilot promising tools. 
* Contribute to internal knowledge bases and GitHub templates that speed future projects. 

 

Qualifications<