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 .

Head of Product

Kindo · Venice, CA

Job title: Head of Product

About Kindo

Kindo.ai is an agent automation platform purpose-built for DevOps and SecOps teams. We help organizations automate tedious, high-friction operational work—securely—using autonomous agents that can run in the background on schedules or triggers. We’re on-prem capable and built with enterprise security controls from day one.

We’re ~40 people, have strong customer traction, and are entering the next phase of growth where product clarity, focus, and execution velocity matter more than ever.

The Role

We’re hiring a Head of Product who will be our sole PM initially—a hands-on, IC-first product leader who can chart direction, translate customer pain into product strategy, and drive high-quality execution with engineering, design, security, and go-to-market. Over time, you’ll lay the foundation for a strong product practice and build a team as the company scales.

Generative AI doesn’t just change what we build—it changes how product is done. This role is for someone who’s excited to prove (and operationalize) what an AI-native product discipline looks like in practice: faster discovery and synthesis, more iteration through working prototypes, fewer heavyweight artifacts, more personalized communication for different audiences, and tighter feedback loops powered by analytics and automation.

This role is ideal for someone who loves being close to customers and the details, but can also zoom out to define a multi-year product arc—and partner directly with the executive team to drive key business decisions.

What You’ll Work On

You’ll own product end-to-end across an agent automation platform, including:

  • Agent automation for DevOps/SecOps across incident response, IAM, vulnerability management, network security, GRC, threat intelligence, red teaming, incident management, infrastructure management, and CI/CD.
  • Agentic tool calling & integrations, including an MCP-server-based ecosystem that lets agents safely take action across enterprise systems.
  • Orchestration at scale, building toward a future where customers run hundreds (eventually thousands) of agents—plus higher-level coordination patterns where users manage hierarchies of agents.
  • Enterprise security & governance controls, especially for customers with strict compliance and regulated requirements.
  • On-prem/self-managed deployments, including constraints that come with regulated environments.

Responsibilities

  • Own the product vision, strategy, and roadmap across platform + workflows; make hard prioritization decisions and keep the team aligned.
  • Serve as the company’s product leader and executive partner, working directly with the CEO/CTO/CSO/CRO/VP Marketing and leadership team on strategy, market direction, and business tradeoffs.
  • Drive customer discovery (security + ops leaders, practitioners, buyers) and translate insights into crisp product requirements and outcomes.
  • Define the platform roadmap for agent execution, orchestration, reliability, and enterprise-grade controls (guardrails, approvals, auditability, policy, observability).
  • Partner deeply with Engineering and Design to ship: write PRDs/specs, run product reviews, unblock execution, and ensure high-quality delivery.

Reinvent the product operating system with generative AI

  • Evolve how product work gets done using AI: faster synthesis of research and customer feedback, automated/agent-assisted analysis of qualitative + quantitative signals, and clearer decision-making with less overhead.
  • Prefer working prototypes and “showable” artifacts (code prototypes, interactive demos, thin specs, living docs) over process-heavy documentation—while maintaining enterprise-grade rigor where it matters (security, governance, reliability, auditability).
  • Build audience-specific narratives and materials (exec, buyer, practitioner, engineering, security/compliance) with tailored messaging that improves alignment and speeds decisions.

Establish operating rhythm and measurement

  • Establish a clear product operating cadence (planning, roadmap reviews, launch readiness, metrics) that scales with the org.
  • Align tightly with GTM on positioning, packaging, pricing inputs, and launch plans—ensuring the product story matches what the market is buying.
  • Build and track product success metrics (adoption, retention, workflow completion, time-to-value, platform reliability, expansion signals).
  • Over time: hire and develop the product team, define roles/processes, and scale product leadership across the company.

What We’re Looking For (Required)

  • 8+ years building product in B2B SaaS and/or enterprise software, with clear ownership of roadmap-to-shipping outcomes.
  • Proven product leadership experience (e.g., Head of Product / VP Product / Director of Product / Group PM), including direct, ongoing partnership with C-level executives (CEO/CTO/CISO/COO) and the ability to drive alignment across Engineering and GTM.
  • Experience building product in the security and/or DevOps domains—you can credibly engage with practitioners and buyers (SOC, IR, IAM, vuln mgmt, infra ops, CI/CD, etc.).
  • Hands-on experience building agentic, AI-enabled platforms and modern LLM-enabled product patterns (tool calling, retrieval/RAG, evals, reliability, human-in-the-loop design).
  • Comfort operating as the sole PM / player-coach while also serving as the company’s product leader—setting direction, driving clarity, and making tradeoffs.
  • Exceptional product judgment and communication: structured thinking, strong writing, crisp decision-making, and the ability to operate effectively amid ambiguity.
  • Track record of strong cross-functional partnership (Engineering, Design, Security/Compliance, Sales, Customer Success).

AI-native product craft

  • You have strong opinions (and real practice) on how generative AI changes product work: how discovery is run, how decisions are made, what artifacts matter, how teams stay aligned, and how you increase velocity without sacrificing quality.
  • You’re comfortable getting “hands-on” with modern tools—whether that’s quickly producing prototypes, iterating on workflows, or building lightweight systems for feedback and analytics—so the team can move faster and learn more.

Nice to Have

  • Experience shipping on-prem / self-managed enterprise software (including regulated or constrained environments).
  • Built or owned platforms with enterprise governance controls (RBAC/permissions, audit trails, policy/approvals, compliance workflows).
  • Experience in or selling to regulated sectors (finance, healthcare, government, critical infrastructure).
  • Prior work on products involving integration ecosystems (connectors, SDKs, API platforms), including quality, versioning, and operational support.
  • Experience with evaluation/measurement for LLM/agent behavior (quality metrics, safety, regression testing, reliability at scale).
  • Ability to prototype in code (or closely partner with engineers to do so) to accelerate iteration and learning.

What Success Looks Like (First 6–12 Months)

  • Establish a clear, focused roadmap that reflects real customer pull and the company’s strategic wedge.
  • Deliver meaningful improvements in agent capability, reliability, and enterprise controls that accelerate adoption/expansion.
  • Create a product operating rhythm that increases clarity and execution velocity across eng/design/GTM.
  • Demonstrably improve how Kindo builds product using AI: faster synthesis, tighter loops, better instrumentation, and more “show, don’t tell” iteration.
  • Define the hiring plan and foundations for a scalable product function.

Why Kindo

  • Build a category-defining agent automation platform for some of the most important (and most painful) workflows in enterprise security and operations.
  • Work on real “automation that takes action,” not just copilots—while staying grounded in governance, safety, and enterprise readiness.
  • High-impact role with broad ownership: strategy, platform direction, customer discovery, and shipping.
  • Help define what “great product” looks like in an AI world—not just for what we deliver to customers, but for how we operate internally.