Engineering Manager - Network Health

Plaid · San Francisco HQ · $216K – $291K · Engineering

Posted 2026-10-14

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Plaid’s Network Health team protects Plaid and our network from fraud and abuse. We build robust, intelligent yet flexible risk platforms and services to empower risk detection, mitigation, and resolution across all Plaid products and applications.

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.

Responsibilities:

- 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.

Nice to have:

- 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

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