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 .

Engineering Manager - Platform

Yurtsai · San Francisco (Remote)

Company overview:

Let’s be real: AI isn’t magic. Legion was built to slice through hype and deliver secure, dependable agentic systems that work alongside the people tackling the world’s most critical challenges. Born from a DoW partnership and trusted by leaders across government and enterprise, Legion embeds intelligence inside complex systems—unlocking data, accelerating human workflows, and hardening mission-critical operations.

From the forward edge to Fortune 500 back-offices, our agentic platform drops AI into the software people already use, optimizing—not replacing—workflows. With world-class collaborators like NVIDIA, HPE, Palantir, and Oracle, we’re building infrastructure that boosts human capability everywhere it runs.

We’re looking for bold thinkers and doers to join us in shaping an AI future that’s secure, grounded, and built to work.


Role Overview:

As an Engineering Manager at Legion Intelligence, you will play a pivotal role in leading and supporting a team of platform and infrastructure engineers. You'll collaborate closely with go-to-market teams to ensure our roadmap aligns with the business's strategic goals. This role requires a deep dive into technical challenges surrounding secure and scalable workflows, driving innovation in product development, and creating a culture of collaboration, innovation, and high-impact.

Key Responsibilities:

  • Own the design, reliability, scalability, and security of the platform infrastructure supporting production Agentic AI systems.
  • Bring an informed perspective and implement best practices around identity and access controls
  • Establish clear patterns for service design, deployment, and inter-service communication.
  • Own system observability (logging, metrics, tracing) and operational readiness.
  • Set technical direction for infrastructure components written in Rust, ensuring performance, safety, and maintainability.
  • Collaborate with go-to-market teams to align roadmap with business goals.
  • Recruit, mentor, and retain high-performing engineers, fostering a culture of innovation and collaboration.
  • Leverage passion for agentic AI and enterprise nuances to deliver solutions that enhance user experience.

Requirements:

  • 2-3+ years of experience hiring and leading teams as an engineering manager.
  • 10+ years of experience as a senior individual contributor, with strong experience in software architecture in enterprise product development.
  • Experience in Rust – our team works almost exclusively in Rust, and you must be comfortable operating in a Rust-heavy environment
  • Hands-on experience with cloud infrastructure and container orchestration with Kubernetes
  • Experience supporting AI/ML platforms, including model serving, agent workflows, and MCP.
  • Excitement and curiosity for 0->1 product development, with a track record of turning innovative ideas into successful features.
  • Attend onsite meetings 2-3 days a month. Location of on-sites may vary
  • Must be eligible to work in the US without sponsorship.

Preferred Qualifications:

  • Knowledge and experience in Agentic AI and its various applications.
  • Experience designing for multi-tenant or on-prem/air-gapped environments.
Compensation Information
$200,000$260,000 USD