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# Staff Software Engineer - Fraud

- **Company:** Mercury Systems, Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $239,000.0 - $298,800.0
- **Contract:** Permanent contract
- **Skills:** Fraud Prevention and Detection, Software Engineering, Backend, Data Pipelines, Glasgow Haskell Compiler
- **Published:** July 2, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b5ec7d529c13d9ae

## About the Role

* Has 7-10+ years of software development experience, with a strong focus on the backend, with a knowledge of or excitement to learn Haskell.
 * Has been an experienced technical lead making architectural decisions in the past and seen the impact of those decisions over time. You should be able to clearly articulate your technical opinions and lay out tradeoffs.
 * Is passionately product-minded and has experience building and shipping new products balancing reliability and velocity.
 * Is someone comfortable driving discussions in areas with ambiguous ownership, approaches them with empathy, and delights in getting outcomes. Our work touches many other teams and areas of the product; you'll have a lot of autonomy and the expectation is you'll use that to seek out ways to have an impact.
 * Is ridiculously helpful, taking initiative to make your coworkers' lives easier by investing time to mentor and proactively share your knowledge and learnings through writings, 1:1s, and team meetings.
 * Experience in fintech, fraud systems, or the broader risk domain is a strong plus.

## Description

We're looking for a Staff Software Engineer to contribute with building the systems and tools that make it all happen-from application approvals to ongoing and enhanced due diligence-ensuring every business that joins Mercury is both safe and their experience is delightful.

As part of this role, you will:

 * Lead the architecture, implementation, and long-term roadmap for core systems which support multiple fraud prevention use cases.
 * Own the end-to-end delivery of large cross-function projects, translating ambiguous high impact problems into strategy and execution, make pragmatic tradeoffs, and drive teams to measurable outcomes.
 * Design, build, and operate highly available, low-latency, backend systems that enable real-time scoring and decisioning for fraud prevention.
 * Partner with Data Science and ML teams to productionize models, build reliable ML data pipelines, and enable real-time model serving.
 * Establish and elevate department level best practices, review designs, drive engineering quality, and act as a trusted advisor on architectural tradeoffs.
 * Mentor and grow engineers, documenting learnings and sharing technical direction through writing, 1:1s, and team meetings
 * Navigate and influence multiple stakeholders, help align teams, communicate tradeoffs to technical and non-technical partners, and independently resolve cross team issues.


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