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Software Engineer Fraud Detection Jobs (NOW HIRING)

Whatnot

Software Engineer, Fraud

San Francisco, CA · On-site

Lead the full architecture of fraud detection, prevention, and intervention systems - spanning ... As our next Software Engineer in Fraud team, you should bring 4+ years of software development ...

Whatnot

Software Engineer, Fraud

San Francisco, CA · On-site

$170K - $230K/yr

Lead the full architecture of fraud detection, prevention, and intervention systems - spanning ... As our next Software Engineer in Fraud team, you should bring 4+ years of software development ...

Ramp

Software Engineer, Fraud & Identity

... Software Engineer to build systems across Fraud, UIM, and Identity ... This role involves developing detection and enforcement capabilities for fraud and account takeover ...

Mercor

Software Engineer, Fraud

New York, NY · On-site

$130K - $500K/yr

Own and build fraud detection and prevention systems across multiple fraud surfaces, including ... What We're Looking For * 4+ years of experience in software engineering. * Preferred: Experience ...

Replit

Staff Software Engineer, Fraud

San Mateo, CA · On-site

Fraud Detection Engineer Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing ...

Replit

Staff Software Engineer, Fraud

Foster City, CA · On-site

We detect and shut down phishing deployments, prevent cryptomining on free-tier infrastructure ... fraud detection * Strong programming skills in Python and/or TypeScript for building detection ...

Replit

Staff Software Engineer, Fraud

Foster City, CA · On-site

$250K - $315K/yr

We detect and shut down phishing deployments, prevent cryptomining on free-tier infrastructure ... fraud detection * Strong programming skills in Python and/or TypeScript for building detection ...

Ramp

Software Engineer, Fraud & Identity

New York, NY · Remote

$168K - $284.90K/yr

You will help build detection and enforcement capabilities for fraud and account takeover, as well ... What You'll Need * 3+ years of software engineering experience (or equivalent). * Strong backend ...

RAMP

Software Engineer, Fraud & Identity

Manhattan, NY · On-site +1

You will help build detection and enforcement capabilities for fraud and account takeover, as well ... What You'll Need * 3+ years of software engineering experience (or equivalent). * Strong backend ...

Replit

Senior Software Engineer, Fraud

Foster City, CA · On-site

$210K - $265K/yr

We detect and shut down phishing deployments, prevent cryptomining on free-tier infrastructure ... fraud detection * Strong programming skills in Python and/or TypeScript for building detection ...

Ramp

Software Engineer, Fraud & Identity

New York, NY · On-site

$168K - $284.90K/yr

You will help build detection and enforcement capabilities for fraud and account takeover, as well ... What You'll Need * 3+ years of software engineering experience (or equivalent). * Strong backend ...

Sidecar

Software Engineer - Fraud

San Francisco, CA

Qualified candidates will be founding members of a new Fraud Engineering team at Sidecar. You will ... Passion for finding problems with software and helping ensure they never happen again. * Easily ...

BNY

Fraud Hub Lead Engineer

Manhattan, NY

$113K - $148.80K/yr

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 ...

BNY

Fraud Hub Lead Engineer

Manhattan, NY · On-site

$112.30K - $147.90K/yr

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 ...

BNY

Fraud Hub Lead Engineer

Manhattan, NY · On-site

$112.30K - $147.90K/yr

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 ...

BNY

Fraud Hub Lead Engineer

Manhattan, NY · On-site

$112.30K - $147.90K/yr

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 ...

BNY

Fraud Hub Lead Engineer

Manhattan, NY · On-site

$112.30K - $147.90K/yr

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 ...

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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 4, 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 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.

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.

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
Infographic showing various Software Engineer Fraud Detection job openings in the United States as of May 2026, with employment types broken down into 84% Full Time, and 16% Part Time. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $104,863 per year, or $50.4 per hour.
Software Engineer, Fraud

Software Engineer, Fraud

Whatnot

San Francisco, CA • On-site

Other

Medical, Dental, Vision, Retirement

This job post has expired today. Applications are no longer accepted.

Job description

Join the Future of Commerce with Whatnot!
Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.
As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.
We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.
Role
The Fraud Experience team builds intelligent, real-time systems that safeguard Whatnot's marketplace from malicious activity. We design, develop, and deploy end-to-end, ML-driven systems that proactively identify and mitigate fraud - blending real-time detection with transparent, user-centered enforcement.
What You'll Do
  • Lead the full architecture of fraud detection, prevention, and intervention systems - spanning machine learning, backend, and client-side components.
  • Build intelligent user graphs to model behavioral patterns, detect collusion networks, and uncover account connectivity at scale.
  • Design, train, and deploy both traditional ML and LLM-powered models to detect fraudulent activity across users, payments, and marketplace interactions.
  • Develop scalable data pipelines and real-time inference systems capable of supporting high-volume, low-latency ML workloads.
  • Create human-in-the-loop systems that continuously refine detection accuracy and adapt to evolving adversarial tactics.
  • Perform deep behavioral and adversarial data analysis to surface emerging fraud trends and drive continuous system improvement.
  • Stay ahead of the curve by translating new insights into adaptive, production-ready systems that evolve as fast as our adversaries.
We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Los Angeles, New York, San Francisco or Seattle hub.
You
People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it.
As our next Software Engineer in Fraud team, you should bring 4+ years of software development experience in high-growth environments, along with a strong bias toward action and impact.
What You'll Bring
  • Bachelor's degree in Computer Science, Statistics, Applied Mathematics, Economics, or a related technical field.
  • 4+ years of software engineering experience building systems for consumer-scale traffic and reliability.
  • 1+ years writing production-grade Python code and working with ML libraries (e.g. PyTorch, LightGBM).
  • 1+ years of experience in machine learning or fraud prevention domains.
  • Deep business intuition and a data-driven mindset - you think critically about how abuse prevention systems affect growth and user experience.
  • Fluency with data tooling, including data warehouses (e.g. Snowflake) and transformation frameworks (e.g. dbt, Dagster).
  • Strong communication skills and the ability to lead initiatives across product areas, collaborating closely with leadership, data science, and product teams.
  • Experience working in a remote-first environment and producing well-tested, reproducible work.
What Sets You Apart
  • You're impact-obsessed - you focus relentlessly on delivering value for users and simplify wherever possible, moving fast without sacrificing quality.
  • You're entrepreneurial and relentless - you prioritize effectively, tackle hard problems with curiosity, and go above and beyond to make things happen.
  • You have a growth mindset and love digging into ambiguous user problems, crafting data-driven solutions, and shipping improvements quickly.
  • Hands-on machine learning or data science experience in production environments.
Benefits
  • Generous Holiday and Time off Policy
  • Health Insurance options including Medical, Dental, Vision
  • Work From Home Support
    • Home office setup allowance
    • Monthly allowance for cell phone and internet
  • Care benefits
    • Monthly allowance for wellness
    • Annual allowance towards Childcare
    • Lifetime benefit for family planning, such as adoption or fertility expenses
  • Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
  • Monthly allowance to dogfood the app
    • All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
  • Parental Leave
    • 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
EOE
Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.

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