Engineering Manager, Network Health & Fraud Risk

Plaid; United States; Remote; USD 180,000 - 280,000; Full time

Benefits offered by this job

Equity compensation

Medical, dental, vision coverage

401(k) plan

Commission opportunities

Job summary

Plaid is building the risk engineering capabilities for Network Health, leading a technical team of engineers and data scientists to detect fraud and abuse across the product portfolio.

The Engineering Manager will shape the vision, roadmap, and metrics for risk platforms, while staying hands-on enough to guide architecture, data analysis, and system design in a fast-evolving environment.

Qualifications

• 8+ years of industry experience, including time as a Staff-level engineer before transitioning into management.
• 2+ years of engineering management experience.
• Track record of setting strategy and executing roadmaps in ambiguous environments while navigating tradeoffs.
• Deep technical judgment in backend and data-intensive systems, with architecture, system design, coding, and data analysis capabilities.
• Experience in risk engineering, fraud detection, abuse prevention, trust and safety, or related domains.

Responsibilities

• Lead a team of 5 engineers and 2 embedded data scientists with clear goals, coaching, and feedback.
• Drive the long-term Network Health strategy and roadmap with product and tech leaders.
• Uphold a high bar for technical quality and delivery velocity, leading by example.
• Dive hands-on into data and tech stack to guide technical decisions based on trends and metrics.

Skills

Team leadership

Engineering management

Strategy & roadmaps

Backend systems

Data analysis

Technical judgment

Risk engineering

Building high performing teams

Job description

Plaid is building the risk engineering capabilities for Network Health, leading a technical team of engineers and data scientists to detect fraud and abuse across the product portfolio.

The Engineering Manager will shape the vision, roadmap, and metrics for risk platforms, while staying hands-on enough to guide architecture, data analysis, and system design in a fast-evolving environment.