KnowBe4

KnowBe4

Talent Acquisition Partner (Position located in Arlington, Virginia)

Arlington, Virginia

Sponsorship not specified$80k-$95kDetected 41 days ago
Agentic AIExcelRecruitingEmployment LawCommunicationCollaborationTime ManagementMentoringMicrosoft Office

Stay score

odds of building a lasting career here

45Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role72
Entry-level history0
PERM / green-card track0
Lottery odds (Level II)66
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~30% per draw at Level II). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

Personalize to your clock →

H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level I · 1×
Level I$65,8941 entry
Level II$85,6342 entries
Level III$105,3943 entries
Level IV$125,1334 entries

$5,634 more — $85,634 — moves this role to Level II and 2 lottery entries. That figure is inside the range the employer already advertised.

Based on the DOL prevailing wage for this occupation and worksite, a base salary of $85,634 would place this position at wage Level II. That figure is within the posted range, and I'd like to target it. This role classifies under "Human Resources Specialists" for prevailing-wage purposes.

DOL prevailing wage, 2026-27 wage year · Human Resources Specialists (13-1071) · Washington-Arlington-Alexandria, DC-VA-MD-WV. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

1 transfer filing in the last year, covering 1 worker. Median labor-condition decision: 8 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

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About the role

  • In addition, the ideal candidate will ensure that our company attracts, hires, and retains the best employees, while growing a strong talent pipeline for future expansion needs.

Responsibilities

  • Perform appropriate sales discovery and closing role plays during the interview process.

Requirements

  • Experience with Gmail and Google Docs
  • Experience with MS Office (Word and Excel)
  • Experience with web browsers (Chrome, Internet Explorer, etc.)
  • Experience with applicant tracking systems
  • Results driven and ability to demonstrate effective hires in a fast paced environment
  • Ability to meet/exceed performance goals

Nice to have

  • Minimum College/University Diploma required, HR background preferred

Compensation

  • The compensation for this position ranges from $80,000 - $95,000, which will vary depending on how well an applicant's skills and experience align with the job description listed above.

Company info

  • KnowBe4 empowers the modern workforce to make smarter security decisions every day.
  • Trusted by more than 70,000 organizations worldwide, KnowBe4 is the pioneer of digital workforce security, securing both AI agents and humans.
  • The KnowBe4 Platform provides attack simulation and training, collaboration security, and agent security powered by AIDA (Artificial Intelligence Defense Agents) and a proprietary Risk Score.
  • The platform leverages 15-years of behavioral data to combat advanced threats including social engineering, prompt injection, and shadow AI.
  • By securing humans and agents, KnowBe4 leads the industry in workforce trust and defense.
  • Arlington positions open to candidates located in the Washington DC area.
  • The Opportunity
  • The Talent Acquisition Partner is responsible for fulfilling company expansion needs by developing and implementing recruiting plans.

This listing is sourced directly from KnowBe4's careers page and normalized into a canonical job model.