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 .

Sales & Business Development Director

Nearfoundation · San Francisco

About NEAR AI

Near.ai is building the future of private AI infrastructure. We’re an early-stage  startup providing a confidential compute inference network that hosts open-source and custom models inside Trusted Execution Environments (TEEs). Our platform offers an OpenAI API–compatible interface, enabling companies to leverage powerful AI capabilities without compromising on privacy.

We serve organizations across financial services, legal, insurance, robotics, entertainment, and government sectors—companies that need verifiable privacy guarantees and can’t use traditional AI providers due to data sensitivity concerns. Unlike expensive alternatives like AWS Nitro Enclaves, we provide cryptographic attestation proving privacy at a significantly lower price point, with high SLAs and custom model hosting capabilities.

The Role

We’re looking for our first Sales & Business Development Director to help build our sales motion from the ground up. You’ll work directly with the Chief Commercial Officer and the founding team to establish repeatable processes for identifying, engaging, and converting privacy-conscious companies into Near.ai customers.

This role blends partnerships, sales development, and early GTM experimentation — but starts with outbound pipeline generation.

What You’ll Do

First 30 Days

  • Immerse yourself in confidential computing, TEEs, and the Near.ai technical value proposition
  • Master our pitch and conduct cold outreach (calls, emails, LinkedIn) to build early pipeline
  • Shadow customer conversations and demos to understand buyer personas and pain points
  • Set up CRM hygiene practices in Attio and establish your prospecting workflow

Days 30–90

  • Book qualified meetings with CISOs, VPs of Engineering, Heads of Infrastructure, and AI/ML leaders
  • Initiate 3+ pilots with target accounts in financial services, insurance, robotics, legal, and tech
  • Build $5M+ of qualified pipeline through multi-touch outbound sequences
  • Begin managing warm inbound leads and supporting partnership development efforts
  • Fine-tune ideal customer profile, partner with marketing to fill top-of-funnel
  • Attend industry conferences and events to build relationships and generate demand

Ongoing Responsibilities

  • Work with the marketing team to own the top of funnel: cold outbound prospecting, lead qualification, and meeting generation
  • Run technical demos and workshops (with product & engineering support as needed)
  • Manage pilots through to conversion, maintaining close contact with prospects
  • Maintain rigorous CRM hygiene and pipeline reporting in Attio
  • Contribute to sales collateral, pitch decks, and outreach templates as we iterate on messaging
  • Travel to conferences and customer meetings to build relationships and close business

Who You Are

Required Experience

  • 5–10 years in B2B sales, with at least 3 years selling infrastructure, cloud compute, or developer tools to technical buyers
  • Proven track record of sales and business development excellence, exceeding quota and building pipeline in early-stage or high-growth environments
  • Strong existing network in target verticals (fintech, legal tech, insurance, AI/ML infrastructure, robotics, or cybersecurity)
  • Technical fluency: ability to understand and articulate TEEs, confidential computing, AI inference, and competitive solutions (AWS Nitro, Azure Confidential Computing)
  • Experience using modern sales tools (Attio/HubSpot/Salesforce, LinkedIn Sales Navigator, Apollo, or similar)

What Makes You Stand Out

  • Experience selling into CISOs, CTOs, VPs of Engineering, or compliance officers at 50–500 person companies
  • Comfortable running technical workshops and discussing ML workloads, attestation, and privacy guarantees
  • Scrappy and founder-mode: you build processes rather than wait for them
  • Thrives in ambiguity and can shift between cold calling, demos, pilots, and conferences in the same week
  • Credibility or relationships in privacy-focused tech communities, AI infrastructure circles, or regulated industries

Personal Attributes

  • Hungry and creative: You find ways to open doors and don’t take no for an answer
  • Technically curious: You enjoy learning complex concepts and translating them into benefits that resonate with buyers
  • Low ego, high urgency: Comfortable as one of the first non-technical hires on a deeply technical team
  • Execution & Process-focused: You move fast, iterate, and measure what matters; you build repeatable, scalable processes
  • Relationship-driven: You build genuine connections and leverage your network to accelerate deals

Our Team & Culture

You’ll join a small, agile, highly technical founding team building at the intersection of AI, privacy, and infrastructure.

We value:

  • In-person collaboration (SF-based)
  • Directness and curiosity
  • Bias toward action and ownership

This is not a corporate environment, you’ll wear multiple hats, challenge assumptions, and contribute far beyond traditional sales responsibilities.

Location & Logistics

  • Location: San Francisco, CA (in-person required)
  • Start Date: February 2025
  • Travel: 10–20% for conferences, customer meetings, and industry events
  • Reporting: Directly to Matt Kummell, Chief Commercial Officer, with close collaboration across the founding team

Our Targets

We’re focused on companies that care deeply about privacy but are not yet bound by heavy compliance frameworks like HIPAA or ISO 27001 (we’re actively working toward these certifications).

Ideal customers include:

  • Financial services using AI on sensitive transaction data
  • Legal & insurance teams analyzing proprietary documents
  • Robotics companies processing telemetry or operational data
  • AI-native tech companies building chat apps, browsers, dev tools
  • Government & entertainment organizations with strict data sovereignty requirements

Target company size: 20–100 employees, primarily in the US and Europe.

Why Now?

AI infrastructure demand is exploding, and privacy requirements are tightening across every industry. Enterprises want alternatives to OpenAI and hyperscalers that offer real, verifiable privacy, strong performance, and sane economics.

Near.ai is positioned at the center of this shift. This role gives you the opportunity to shape how this technology enters the market—at exactly the right moment.

How to Apply

Submit your resume along with:

  1. A brief note (2–3 paragraphs) on why you’re excited about Near.ai and how your experience/network positions you for success

  2. 3–5 companies or contacts you’d target in your first 30 days - and why

Top candidates will also receive a take-home exercise to assess pipeline-building and outbound strategy.

We value

  • ECOSYSTEM-FIRST: always put the health and success of the ecosystem above any individual's interest
  • OPENNESS: operate transparently and consistently share knowledge to build open communities
  • PRAGMATISM OVER PERFECTION: find the right solution not the ideal solution and beat dogmatism by openly considering all ideas
  • MAKE IT FEEL SIMPLE: strive to make the complex feel simple so the technology is accessible to all
  • GROW CONSTANTLY: learn, improve and fail productively so the project and community are always becoming more effective

NEAR is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. NEAR is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. To request reasonable accommodation, please let your recruiter know during the interview process.