Company Profile
VaultPay builds payment processing infrastructure for enterprise fintech applications. Founded in 2022, they had raised a $28M Series B and were preparing to launch a new real-time payments product that required a significant expansion of their engineering team. At the time, VaultPay had 65 employees, 30 of whom were engineers.
Their engineering stack included Go, Rust, and TypeScript for backend services, with PostgreSQL and Redis for data storage. They needed specialists in distributed systems, payment protocols, and security - a notoriously difficult talent segment to recruit in.
The Challenge
VaultPay was competing for the same small pool of fintech engineers as Stripe, Plaid, and Square. Their previous hiring cycle had taken an average of 38 days from job posting to accepted offer. For specialized roles like distributed systems engineers and payment protocol experts, the timeline stretched to 52 days. In that window, candidates were receiving and accepting competing offers.
The numbers were painful. In the six months before adopting WorkSwipe, VaultPay had spent $412,000 on recruiting to fill 11 engineering positions. That included two agency recruiters at $18,000-$22,000 per placement, LinkedIn Recruiter at $8,500/year per seat for three seats, and Indeed Sponsored listings averaging $3,200/month. Cost per hire was averaging $37,400.
Their VP of Engineering estimated that each unfilled position was costing $4,200 per week in delayed product development. With 20 open positions, the delay cost was accumulating at roughly $84,000 per week.
"We had the budget, the interesting problems, and competitive compensation. What we did not have was speed. Every week a senior engineer position sat open, our product launch slipped further. We lost our top candidate for the payments team lead to a competitor who made an offer 9 days faster than we did."
The Solution
VaultPay's talent acquisition lead discovered WorkSwipe through a comparison with Hired. After a 45-minute technical onboarding session, they had all 20 positions configured with detailed tech stack requirements, team culture descriptions, and salary transparency ranges.
Launch and First Matches
20 engineering positions posted with granular skill requirements. WorkSwipe's 4D matching algorithm surfaced 87 mutual matches in the first 10 days. Each match meant both the candidate and VaultPay had shown genuine interest, eliminating cold outreach entirely.
Technical Interview Sprint
VaultPay compressed their interview process from 4 rounds to 2 for WorkSwipe candidates. Because mutual matching had already validated interest and basic qualification, they eliminated the recruiter screen entirely. 52 technical interviews conducted in 2 weeks.
Offers and Acceptances
14 offers extended, 13 accepted (93% acceptance rate). The salary transparency built into WorkSwipe profiles meant zero offers were rejected on compensation grounds. VaultPay opened 6 additional positions based on pipeline quality.
Final Push and Target Hit
7 more offers extended for the remaining and newly opened positions. 20 total engineers hired across backend, infrastructure, security, and frontend roles. Three of the hires were senior engineers who had previously passed on recruiter outreach from VaultPay.
Before and After
| Metric | Before WorkSwipe | With WorkSwipe |
|---|---|---|
| Average Time-to-Offer | 38 days | 11 days |
| Cost Per Hire | $37,400 | $10,850 |
| Offer Acceptance Rate | 64% | 93% |
| Interview-to-Offer Rate | 28% | 72% |
| 6-Month Retention | 82% | 95% |
| Candidates Lost to Competitors | 8 in 6 months | 1 in 60 days |
| Recruiter Hours Per Hire | 34 hours | 9 hours |
Roles Filled
The 20 engineering hires spanned four functional areas, each with distinct technical requirements that WorkSwipe's matching algorithm handled through granular skill profiling.
- Backend engineers (8 hires): Go and Rust developers with distributed systems experience. These were the most competitive roles. WorkSwipe's salary transparency feature proved critical - candidates saw the $180K-$220K range upfront, which attracted senior talent who would not have responded to vague "competitive compensation" listings.
- Infrastructure and DevOps (5 hires): Kubernetes, Terraform, and AWS specialists. WorkSwipe matched on specific cloud certifications and infrastructure scale experience. Average time-to-offer for this group was just 9 days.
- Security engineers (3 hires): The hardest segment to fill. Payment security specialists are rare. WorkSwipe's algorithm identified candidates with relevant compliance experience (PCI-DSS, SOC 2) who were not actively applying to jobs but had marked themselves as open to opportunities.
- Frontend engineers (4 hires): React and TypeScript developers for VaultPay's merchant dashboard. The fastest cohort to fill - all 4 positions closed within 3 weeks.
"The mutual matching model changed our entire approach to engineering hiring. On LinkedIn, we were sending cold InMails to candidates who were already drowning in recruiter messages. On WorkSwipe, every conversation started with mutual interest. Our offer acceptance rate went from 64% to 93% - that alone justified the switch."
Financial Impact
Direct recruiting savings: Hiring 20 engineers through traditional channels at $37,400 per hire would have cost $748,000. Through WorkSwipe, total cost was $217,000 - a savings of $531,000.
Velocity savings: By filling positions 27 days faster on average, VaultPay recovered an estimated $2.3M in product development velocity. The real-time payments product launched on schedule, 6 weeks ahead of what the delayed hiring timeline would have allowed.
Retention value: The 95% six-month retention rate (vs. 82% previously) means VaultPay avoided approximately 3 replacement hiring cycles, saving an additional $112,000 in rehiring costs.