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# Engineering Manager - Network Health

- **Company:** Plaid's Network
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Fraud Prevention and Detection, Machine Learning, Backend
- **Published:** October 18, 2026
- **Apply:** https://www.dice.com/job-detail/45884af5-6e13-4cf0-bdc6-2db0878cdac4

## About the Role

* 8+ years of industry experience, that includes time as a Staff-level engineer before transitioning into management.
 * 2+ years of engineering management experience
 * A track record of setting strategy and executing against roadmaps in ambiguous environments while navigating business, product, and technical tradeoffs.
 * Deep technical judgment in backend and data-intensive systems, with the ability to engage directly in architecture, system design, coding, and data analysis.
 * Experience in risk engineering, fraud detection, abuse prevention, trust and safety, or a related domain.
 * Track record of building and growing high performing engineering teams

## Description

As Engineering Manager for Network Health, you will lead a growing, deeply technical team responsible for risk engineering at Plaid. You will set the long-term strategy and roadmap, translate evolving fraud scenarios and business requirements into technical priorities, and drive execution with a high technical bar. You will manage and grow software engineers, partner closely with embedded data scientists and machine learning engineers, and work hands-on with the data to identify trends and opportunities. This role is well suited to a high-agency leader who thrives in ambiguity and wants to remain close to the work while shaping a critical new team., * You'll lead a team of 5 engineers and 2 embedded data scientists, developing them through clear goal setting, coaching, and feedback.

 * You'll drive the long-term Network Health strategy and roadmap, in close partnership with technical and product leaders across Plaid
 * You'll uphold a high bar for technical quality and delivery velocity, leading by example.
 * You'll dive hands-on into the data and tech stack to understand current metrics, trends, and opportunities - then use those to guide the team's technical decisions.