IT & AI Engineering Staffing

How a Healthcare Technology Company Shipped Its AI Platform 3 Months Early — by Closing 5 Critical Engineering Roles in 21 Days

Challenge

Talent gap blocking a product launch with $4M in customer commitments riding on it

MedBridge Health Technologies

120 employees, Series B, Seattle, WA

Key Outcomes
VERIFIED
Roles Filled
5 of 5
Days to All Placements21
Resumes Reviewed by Client (vs. 40+ with prior agencies)17
Early Platform Launch3 Mo.
Contract Value Protected$4M+
Industry
Healthcare Technology / Digital Health

5 of 5

Roles Filled

Days to All Placements

Resumes Reviewed by Client (vs. 40+ with prior agencies)

3 Mo.

Early Platform Launch

$4M+

Contract Value Protected

Company Overview

MedBridge Health Technologies had a problem that many rapidly growing health tech companies face: an aggressive product commitment and a team that wasn't big enough to deliver it on time. Their flagship product — a predictive patient risk platform that integrated EHR data with proprietary ML models to flag high-risk patients before hospitalization — had secured three large health system pilots. Combined contract value: $4M+ in the first year alone.

The Challenge

The Problem
That Needed Solving

The platform was 60% complete, and the engineering team needed to double in size to hit the contractual launch date 14 weeks away. They had tried two generalist staffing agencies. After four weeks, they had received 40+ resumes, interviewed 12 candidates, and made zero hires. The agencies didn't understand what ML engineers actually did — let alone what it meant to work with healthcare data.

Roles Required

2 Senior ML Engineers with healthcare data experience (HL7, FHIR familiarity preferred)

1 Data Engineer (Python, PySpark, Azure Data Factory)

1 Cloud Architect (Azure-focused, HIPAA compliance experience)

1 Frontend Engineer (React, data visualization for clinical dashboards)

Zaruda's Solution

How We Delivered
the Result

Day 1

Technical Intake with Engineering Leadership

Zaruda's recruiting team held a 90-minute technical intake call with MedBridge's VP of Engineering and Head of Data Science. We didn't just review the JDs — we discussed the actual architecture, tooling choices, team working style, and the clinical domain context that candidates would need to succeed.

Day 3

Initial Candidate Presentation

Zaruda presented 3 pre-screened candidates for the two ML Engineer roles — all having passed Zaruda's technical screening, which included a review of past healthcare ML project work, a discussion of FHIR/HL7 data modeling experience, and a 30-minute technical problem-solving conversation with a Zaruda ML engineer.

Days 5–10

Remaining Role Presentations

By Day 10, Zaruda had presented screened candidates for all five roles. Every candidate had already cleared Zaruda's technical bar.

Days 10–21

Interviews, Offers, Acceptances

MedBridge conducted a streamlined 2-stage interview process (Zaruda helped them redesign their interview process to reduce time-to-decision without sacrificing quality). All five offers were extended by Day 18. All five were accepted by Day 21.

Detailed Results

The Numbers That
Moved the Business

MetricResult

Roles filled5 of 5

Days to all placements21

Resumes reviewed by client17 (vs. 40+ with previous agencies)

Candidates who didn't pass Zaruda screening0 reached client

Platform launch vs. contractual deadline3 months early

Contract value protected$4M+

MedBridge shipped their predictive risk platform 3 months ahead of their contractual commitment date. The expanded team hit their velocity targets from week 2, and two of the five Zaruda-placed engineers have since been converted to permanent employees.

“

We'd wasted a month with other agencies before Zaruda. In the first intake call, it was immediately obvious that Zaruda's team actually understood what our engineers do. Every candidate they sent us was legitimate — we made five hires and every single one of them is performing well. That doesn't happen with generalist firms.

VP of Engineering, MedBridge Health Technologies [Fictional]