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Software Engineer Fraud Detection Jobs in Renton, WA

ProRata

Principal Program Manager

Bellevue, WA · On-site +1

$220K - $260K/yr

... and fraud detection systems. * Partner closely with the Principal Software Engineering Manager (Tech Lead) and engineering teams to define technical roadmaps, break down epics into actionable ...

ProRata.ai

Principal Program Manager

Bellevue, WA · On-site

$260K/yr

... and fraud detection systems. * Partner closely with the Principal Software Engineering Manager (Tech Lead) and engineering teams to define technical roadmaps, break down epics into actionable ...

ProRata.ai

Principal Program Manager

Bellevue, WA · On-site

$220K - $260K/yr

... and fraud detection systems. * Partner closely with the Principal Software Engineering Manager (Tech Lead) and engineering teams to define technical roadmaps, break down epics into actionable ...

Amazon

Software Development Manager, Amazon Neptune

Seattle, WA · On-site

$140K - $185K/yr

Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs ... You will enable and support the engineers on the team to design and deliver new features that drive ...

Amazon

Software Development Manager, Amazon Neptune

Seattle, WA · On-site

$140K - $185K/yr

Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs ... You will enable and support the engineers on the team to design and deliver new features that drive ...

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All JobsSoftware Engineer Fraud Detection JobsSoftware Engineer Fraud Detection Jobs in Renton, WA

Software Engineer Fraud Detection information

See Renton, WA salary details

$27K

$118K

$212.6K

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

As of Aug 18, 2026, the average yearly pay for software engineer fraud detection in Renton, WA is $117,952.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,100.00 and $135,000.00 per year, depending on experience, location, and employer.

What does a software engineer 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.

How does a software engineer 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 are the key skills and qualifications needed to thrive as a software engineer 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.

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 job categories do people searching Software Engineer Fraud Detection jobs in Renton, WA look for?

The top searched job categories for Software Engineer Fraud Detection jobs in Renton, WA are:

Software Engineer Fraud Detection jobs near you

AI Product Manager - Order-to-Cash Automation & Intelligence

Inabia Software & Consulting Inc.

Redmond, WA • On-site

$75 - $80/hr

Full-time

Re-posted 3 days ago

Job description

  • AI Product Manager – Order-to-Cash Automation & Intelligence
  • Location: Redmond, WA (Onsite – 5 Days per Week)
  • Employment Type: Long-Term Contract (W-2 Only)
  • Work Authorization: U.S. Citizen or Green Card Holder Only (No Sponsorship Available)
  • Compensation: $75.00 - $80.00 per hr.
Overview
Inabia Solutions & Consulting is seeking an experienced AI Product Manager to drive the strategy, development, and deployment of AI-powered solutions that enhance and automate critical Order-to-Cash (O2C) business processes.
This role will focus on identifying opportunities to leverage Generative AI, Machine Learning, Intelligent Automation, and Agentic AI capabilities to improve operational efficiency, customer experience, fraud detection, billing accuracy, tax compliance, order processing, and revenue lifecycle management.
The ideal candidate combines strong Product Management expertise with practical experience implementing AI-driven business solutions within large-scale eCommerce, subscription, telecommunications, financial services, or technology environments.
This is a highly visible role requiring close collaboration with Product, Engineering, Finance, Operations, Risk, Fraud, Tax, Compliance, and Customer Experience teams.
Key Responsibilities
AI Product Strategy
  • Identify high-value opportunities to apply AI and automation across the Order-to-Cash lifecycle.
  • Develop AI product roadmaps aligned with business objectives and operational efficiency goals.
  • Prioritize AI initiatives based on customer impact, risk reduction, revenue protection, and operational scalability.
  • Build business cases and success metrics for AI-powered solutions.
Order-to-Cash Process Optimization
Drive AI capabilities across:
  • Customer onboarding
  • Product catalog management
  • Pricing and promotions
  • Order validation
  • Fraud detection and prevention
  • Billing and invoicing
  • Subscription lifecycle management
  • Tax determination and compliance
  • Returns and refunds
  • Revenue assurance and reconciliation
  • Customer support automation
Product Delivery & Execution
  • Define product requirements, user stories, acceptance criteria, and success metrics.
  • Partner with Engineering teams to design, build, test, and deploy AI-powered applications and tools.
  • Collaborate with Data Science, Machine Learning, and Analytics teams to operationalize AI models.
  • Lead Agile ceremonies and product planning activities.
  • Manage product lifecycle from ideation through deployment and continuous improvement.
AI & Intelligent Automation
Support initiatives involving:
  • Generative AI (LLMs)
  • AI Assistants and Copilots
  • Agentic AI workflows
  • Intelligent Document Processing
  • Predictive Analytics
  • Fraud Detection Models
  • Conversational AI
  • Recommendation Engines
  • Workflow Automation
  • Customer Service Automation
Stakeholder Management
  • Partner with Finance, Tax, Compliance, Fraud Operations, Legal, Customer Experience, and Engineering leadership.
  • Present AI product strategy, roadmap progress, risks, and business outcomes to executive stakeholders.
  • Drive alignment across technical and business teams.
Required Qualifications
  • 7+ years of Product Management experience.
  • 3+ years leading AI, Machine Learning, Intelligent Automation, or Generative AI initiatives.
  • Experience managing products supporting Order-to-Cash, eCommerce, Billing, Payments, Subscription Management, Revenue Operations, or Financial Systems.
  • Strong experience writing:
    • Product Requirements Documents (PRDs)
    • Business Requirements Documents (BRDs)
    • User Stories
    • Acceptance Criteria
  • Experience working in Agile/Scrum environments.
  • Strong understanding of business process automation and workflow optimization.
  • Excellent communication and stakeholder management skills.
  • Experience collaborating with Engineering, Data Science, and Business Operations teams.
Preferred Qualifications
  • Experience supporting Amazon, Kuiper, Microsoft, Comcast, Verizon, T-Mobile, or similar high-scale organizations.
  • Experience with:
    • OpenAI
    • Anthropic Claude
    • Amazon Bedrock
    • Azure OpenAI
    • AWS AI Services
    • Google Vertex AI
  • Knowledge of Fraud Operations, Billing, Tax, Revenue Assurance, or Financial Compliance.
  • Experience building AI copilots, agents, or intelligent workflow tools.
  • Familiarity with Jira, Confluence, SQL, Tableau, Power BI, or similar platforms.

 

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