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Software Engineer Fraud Detection Jobs in Hackensack, NJ

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 ...

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 ...

Fraud Hub Lead Engineer

New York, NY ยท On-site

$112K - $147K/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 ...

Fraud Hub Lead Engineer

Manhattan, NY

$113K - $148K/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 ...

Fraud Hub Lead Engineer

Manhattan, NY ยท On-site

$113K - $148K/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 ...

Fraud Hub Lead Engineer

Manhattan, NY ยท On-site

$112K - $148K/yr

... fraud detection, prevention, and response platforms while driving AI-first solutions ... Required : โ€ข 10+ years of software engineering experience, with at least 5 years delivering Fraud ...

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 ...

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 ...

Architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral analysis * Develop and maintain end-to-end ML pipelines: data ingestion, feature engineering, model ...

Staff Machine Learning Engineer

Manhattan, NY ยท On-site

$180K - $220K/yr

... software engineers, fostering best practices and innovation. Minimum Qualifications * 5+ years of experience building ML or AI systems in production; at least 2+ in fraud, risk, or anomaly detection ...

... software engineers, fostering best practices and innovation. Minimum Qualifications * 5+ years of experience building ML or AI systems in production; at least 2+ in fraud, risk, or anomaly detection ...

Fraud detection and platform integrity - identity verification, abuse prevention, risk scoring, and ... software engineering teams * Experience leading teams through periods of significant scale ...

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Software Engineer Fraud Detection information

See Hackensack, NJ salary details

$26.2K

$114.4K

$206.1K

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

As of Aug 2, 2026, the average yearly pay for software engineer fraud detection in Hackensack, NJ is $114,368.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,900.00 and $130,900.00 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.
Infographic showing various Software Engineer Fraud Detection job openings in Hackensack, NJ as of July 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $114,368 per year, or $55 per hour.

Software Engineer, Fraud & Identity

Ramp

New York, NY โ€ข Remote

$168K - $284K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago


Job description

About Ramp

Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.

The problems are high-stakes, data-dense, and unforgiving.

We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.

The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.

If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.

About the Role

We are hiring a Software Engineer to build systems across Fraud, UIM (User & Identity Management), and Identity. This role sits at the intersection of security, risk decisioning, and product experience. You will help build detection and enforcement capabilities for fraud and account takeover, as well as the identity primitives that power authentication, authorization, and safe account access.

This work is deeply cross-functional. You will partner closely with Fraud Ops, Risk Strategy, Security, Product, and Data to ship improvements that are measurable in loss reduction, attack containment, and user experience.

What You’ll Do
  • Build and evolve backend services that detect and prevent fraud across multiple surfaces, including account access and money movement.

  • Develop enforcement and response tooling that enables fast, safe actions such as identity locks, business locks, payment freezes, and other containment levers.

  • Improve protections against account takeover (ATO), including risk-based step-ups, monitoring, and targeted friction controls (for example “under attack” style controls and MFA surge detection/alerting).

  • Design and operate high-signal systems with strong observability: metrics, dashboards, alerting, and playbooks for incidents and fraud campaigns.

  • Partner with UIM/Identity stakeholders to strengthen authentication and identity foundations (roles, permissions, identity state, and related platform primitives).

  • Drive end-to-end delivery: technical design, implementation, rollout strategy, and iteration based on outcome metrics.

What You’ll Need
  • 3+ years of software engineering experience (or equivalent).

  • Strong backend engineering fundamentals (APIs, distributed systems, data modeling, reliability).

  • Experience building data-informed detection or decisioning systems (rules engines, scoring, anomaly detection, or similar), or strong interest in learning in this domain.

  • Proven ability to operate production systems: debugging, incident response, and improving on-call quality through instrumentation and automation.

  • Strong cross-functional communication skills and comfort working with product and operations partners.

Nice to Have

  • Experience in fraud, risk, identity, authentication, authorization, abuse prevention, or security engineering.

  • Familiarity with payments rails, card transaction risk, or account security patterns.

  • Experience building internal tools for operations teams (case management, investigation, enforcement workflows).

Benefits available to all full-time Ramp employees (Global)
  • Flexible PTO

  • Centralized home-office equipment ordering

  • Health and wellness stipend

  • Budget for intra-office travel

  • Weekly coffee stipend

United States
  • 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents

  • One Medical annual membership

  • 401(k), including employer match on contributions made while employed by Ramp

  • Fertility HRA (up to $10,000 per year)

  • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay

  • Pet insurance

  • In-office perks: lunch, snacks, drinks, and more

  • Relocation support to NYC or SF (as needed)

Canada
  • Group medical, dental, and vision coverage through Sun Life

  • Life, AD&D, and disability coverage

  • Fertility drug coverage (up to $4,000 lifetime)

  • Group Retirement Plan with employer match (RRSP + DPSP)

  • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay

  • Employee Assistance Program and virtual care through Lumino Health

United Kingdom
  • Private medical insurance through Freedom Elite

  • Virtual GP and at-home care via eMed x Livi

  • Workplace pension through Penfold, with salary sacrifice option

  • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay

Referral Instructions

If you are being referred for the role, please contact that person to apply on your behalf.

 
Other notices

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

 

Beware of recruiting scams: Ramp will only contact you through official @Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.

 

Ramp Applicant Privacy Notice

Compensation Range: $168K - $284.9K