ZipRecruiter

Log In

1

Software Engineer Fraud Detection Jobs (NOW HIRING)

Mercury

Staff Software Engineer - Fraud

They are seeking a Staff Software Engineer to lead the architecture and implementation of fraud prevention systems, ensuring a delightful experience for businesses applying for accounts.

Twilio

Senior Software Engineer

$125K - $165K/yr

Build and own fraud detection capabilities for Stytch's fraud platform on Twilio-go deep on browser and device internals for complex signal collection to improve identification of bad actors and keep ...

BNY

Fraud Hub Lead Engineer

Pittsburgh, PA · On-site

$99K - $131K/yr

Required : • 10+ years of software engineering experience, with at least 5 years delivering Fraud ... detection, or real-time risk decisioning. • Demonstrated success leading and scaling global ...

BNY

Fraud Hub Lead Engineer

Lake Mary, FL · On-site

$89K - $118K/yr

Required : • 10+ years of software engineering experience, with at least 5 years delivering Fraud ... detection, or real-time risk decisioning. • Demonstrated success leading and scaling global ...

BNY

Director, Fraud Hub Lead Engineer

Manhattan, NY

This role serves as the firmwide engineering authority for Fraud detection, prevention, and ... Qualifications & Experience Required * 10+ years of software engineering experience, with at least ...

next page

Showing results 1-20

All JobsSoftware Engineer Fraud Detection Jobs

Software Engineer Fraud Detection information

See salary details

$24K

$104.9K

$189K

How much do software engineer fraud detection jobs pay per year?

As of Jun 28, 2026, the average yearly pay for software engineer fraud detection in the United States is $104,863.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $120,000.00 per year, depending on experience, location, and employer.

What does a Software Engineer in Fraud Detection do?

A Software Engineer in Fraud Detection designs and develops systems to identify and prevent fraudulent activities within digital platforms, such as banking or e-commerce environments. They build algorithms to analyze user behavior, detect anomalies, and flag suspicious transactions in real time. Their work often involves machine learning, big data analysis, and close collaboration with data scientists and security teams to continuously improve fraud detection accuracy. These engineers play a key role in protecting businesses and customers from financial loss and cybercrime.

What is the difference between Software Engineer Fraud Detection vs Data Scientist Fraud Detection?

AspectSoftware Engineer Fraud DetectionData Scientist Fraud Detection
Required CredentialsBachelor's in CS or related field, programming skillsBachelor's or higher in CS, Statistics, or Data Science
Work EnvironmentDevelops fraud detection systems, writes code, implements algorithmsAnalyzes data, builds models, interprets results
Employer & Industry UsageFinancial institutions, fintech, e-commerceFinancial services, tech companies, insurance
Common Search & ComparisonFocuses on software development for fraud detectionFocuses on data analysis and modeling for fraud detection

While both roles work in fraud detection, Software Engineer Fraud Detection primarily develops and maintains detection systems through coding, whereas Data Scientist Fraud Detection analyzes data and builds models to identify fraudulent activity. Both roles often collaborate but differ in their core focus and skill sets.

What are the key skills and qualifications needed to thrive as a Software Engineer in Fraud Detection, and why are they important?

To thrive as a Software Engineer in Fraud Detection, strong programming skills (such as Python, Java, or Scala), a solid understanding of algorithms, data structures, and experience with machine learning or statistical analysis are generally required, often supported by a degree in computer science or a related field. Familiarity with big data platforms (like Hadoop or Spark), real-time analytics systems, and fraud detection tools or frameworks is typically expected. Analytical thinking, problem-solving abilities, and effective communication are key soft skills that differentiate top performers in this field. These skills are crucial for developing robust systems that can quickly identify and prevent fraudulent activities, protecting both users and organizations.

How does a Software Engineer in Fraud Detection typically collaborate with data scientists and analysts to identify fraudulent activity?

Software Engineers in Fraud Detection work closely with data scientists and analysts to build, refine, and deploy systems that detect and prevent fraud. While data scientists may develop models and identify patterns from large datasets, engineers are responsible for integrating these models into scalable, real-time systems within the company's technology stack. Regular communication and joint problem-solving are essential, as engineers must understand the logic behind models and analysts' findings to ensure accurate implementation and continuous improvement. This collaborative environment helps create robust fraud detection mechanisms that adapt to evolving threats.
More about Software Engineer Fraud Detection jobs
What cities are hiring for Software Engineer Fraud Detection jobs? Cities with the most Software Engineer Fraud Detection job openings:
What states have the most Software Engineer Fraud Detection jobs? States with the most job openings for Software Engineer Fraud Detection jobs include:
What job categories do people searching Software Engineer Fraud Detection jobs look for? The top searched job categories for Software Engineer Fraud Detection jobs are:
Software Engineer Fraud Detection jobs near you

Staff Software Engineer - Fraud

Mercury

San Francisco, CA • On-site, Remote

Full-time

Posted 25 days ago

Job description

Every new business that applies to Mercury is like a new star appearing in the night sky. On its own, it's a single point of light. But when we look closer, patterns emerge-data trails from partners, filings, founders, and financial histories-all connecting to form a larger constellation.
That's what our Risk product engineering teams do at Mercury. We guide thousands of business applications through our systems-each one unique, each one needing a smooth and trustworthy landing. The challenge: keep everything moving fast without compromising safety. Every day, our work helps founders open their first account, launch their next idea, and accelerate their growth like rocketships.
Our mission is to build the intelligent, automated systems and operational tools that make this possible-where machine learning, AI, and human judgment work seamlessly together to power the next generation of business banking*. We use intelligence to detect risks earlier, make real-time decisions with confidence, and enable instant, delightful account approvals that keep pace with the builders we serve.
When we do it right, the result is quiet brilliance: onboarding that feels effortless, even though it's powered by galaxies of data, precision, and care.
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.

The ideal candidate for 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.

If this role interests you, we invite you to explore our public demo at personal-demo.mercury.com.
The total rewards package at Mercury includes base salary, equity (stock options), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate's experience, expertise, geographic location, and internal pay equity relative to peers.
Our target new hire base salary ranges for this role are the following:
  • US employees (any location): $239,000 - $298,800
  • Canadian employees (any location): CAD 225,900 - 282,400

*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.
Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.
#LI-RA1

Apply