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Software Engineer Fraud Detection Jobs in Utah (NOW HIRING)

Red Cat Holdings, Inc.

Data Engineer

Salt Lake City, UT · On-site

$105K - $126K/yr

Add data quality checks (tests, constraints, anomaly detection, reconciliation checks) and fix root ... This position requires direct or indirect access to hardware, software, technology or technical ...

RED CAT HOLDINGS

Data Engineer

Salt Lake City, UT · On-site

$105K - $126K/yr

Add data quality checks (tests, constraints, anomaly detection, reconciliation checks) and fix root ... This position requires direct or indirect access to hardware, software, technology or technical ...

Bread Financial

Senior Staff Agentic AI Engineer

Draper, UT · On-site +1

$99K - $134K/yr

Job Summary The Senior Staff Software Engineer - Agentic AI will design and deliver core agent ... detection, and decisioning. The role includes implementing deterministic paths where needed ...

LVT

Sensor Integration Engineer II

American Fork, UT

$93K - $125K/yr

Product & Software Excellence: We were named one of The Software Report's Top 100 Software ... quality, detection range, low-light and IR night vision performance--and prove it holds in rain ...

LVT

Sensor Integration Engineer II

American Fork, UT · On-site

$93K - $125K/yr

Product & Software Excellence: We were named one of The Software Report's Top 100 Software ... quality, detection range, low-light and IR night vision performance-and prove it holds in rain ...

Adobe

Senior Security Automation Engineer

Lehi, UT

$97K - $128K/yr

You'll partner with Detection Engineering to turn new detection rules into working response ... WHAT YOU NEED TO SUCCEED Required: * 7+ years in security engineering, software engineering, or ...

Autonomous Solutions

Perception Engineer IV

Mendon, UT · On-site

$100 - $130/hr

Lead complex perception features involving object detection, classification, segmentation, tracking ... Integrate perception software with ASI's autonomous vehicle platforms, embedded computing systems ...

Octanner

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

Tanner is the global leader in software and services that improve workplace culture through ... Implemented AI safety and evaluation pipelines covering bias detection, PII leakage, faithfulness ...

OC Tanner

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

Tanner is the global leader in software and services that improve workplace culture through ... Implemented AI safety and evaluation pipelines covering bias detection, PII leakage, faithfulness ...

Tech9

QA Engineer

Sandy, UT · On-site

$70 - $90/hr

Work with business stakeholders, product specialists, and software engineers to understand business ... detection.* Collaborate with the QA manager and other stakeholders to implement and improve QA ...

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All JobsSoftware Engineer Fraud Detection JobsSoftware Engineer Fraud Detection Jobs in Utah

Software Engineer Fraud Detection information

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 are popular job titles related to Software Engineer Fraud Detection jobs in Utah?

For Software Engineer Fraud Detection jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Software Engineer Fraud Detection jobs in Utah look for?

The top searched job categories for Software Engineer Fraud Detection jobs in Utah are:

What cities in Utah are hiring for Software Engineer Fraud Detection jobs?

Cities in Utah with the most Software Engineer Fraud Detection job openings:

Software Engineer Fraud Detection jobs near you

Data Engineer

Red Cat Holdings, Inc.

Salt Lake City, UT • On-site

$105K - $126K/yr

Other

Re-posted 10 hours ago

Job description

Position Summary
We're hiring a Data Engineer to build our data foundation from the ground up.
Today, our data lives across transactional databases, SaaS tools, and external APIs. Over the next few months, you'll help us stand up our first analytics data warehouse and build the ETL/ELT pipelines that keep it accurate, fresh, and easy to use.
You won't be doing this alone-you'll work closely with stakeholders (Product, Ops, Finance, and Analytics) and with engineering teammates to make pragmatic choices and ship value quickly.
Essential Duties and Responsibilities
Building Pipelines and Ingestion
  • Build and maintain ETL/ELT pipelines that ingest data from multiple sources (e.g., internal DBs, SaaS tools, and third-party APIs), and keep them running reliably.
  • Implement scheduling/orchestration, retries, and alerting so failures are visible and recoverable.
  • Design pipelines using incremental processing patterns for scalability and cost efficiency.

Standing up the Warehouse and Models
  • Help set up our first cloud data warehouse (e.g., Snowflake or BigQuery) and the initial schema/layout.
  • Add data quality checks (tests, constraints, anomaly detection, reconciliation checks) and fix root causes when numbers look wrong.
  • Create lightweight observability: freshness/SLAs, pipeline run monitoring, and basic lineage documentation.
  • Make thoughtful tradeoffs between performance, usability, and maintainability.

Collaboration and Enablement
  • Work with stakeholders to translate questions into durable datasets (not one-off queries).
  • Document sources, models, and assumptions so teammates can self-serve and onboard quickly.
  • Participate in a reasonable support/on-call rotation once the stack is live.
Required Qualifications
  • Bachelor's degree in computer science, data engineering, information systems, or equivalent technical degree.
  • 3+ years of data engineering experience, specifically in managing a data warehouse.
  • Strong SQL skills (joins, window functions, building reliable transformation logic).
  • Comfortable in Python (or a similar language) for pipeline code, automation, and data tool glue.
  • Understanding of data warehousing basics: tables, partitions (where relevant), incremental loads, and why modeling choices matter.
  • Some hands-on exposure to ETL/ELT or pipelines in production or in a substantial project/internship (we care about proof you can ship and debug).
  • Solid engineering habits: Git, readable code, and a willingness to write things down.
Additional Desired Qualifications
  • dbt experience (models + tests + docs) or the ability to ramp quickly.
  • Orchestration experience (Airflow, Dagster, Prefect, or similar).
  • Experience with a cloud data warehouse (Snowflake, BigQuery, Redshift).
  • Experience ingesting data from APIs and messy SaaS exports (rate limits, pagination, schema drift, deduping).
  • Familiarity with basic data quality/observability practices (freshness checks, anomaly detection, monitoring/alerting).
Physical Requirements and Working Conditions
  • Must be able to walk, stand, and navigate large indoor and outdoor facilities for extended periods of time.
  • Ability to lift, carry, and move materials and equipment weighing up to 25 lbs on a regular basis.
  • Use of personal protective equipment (PPE) may be required in designated areas or when performing specific tasks, in accordance with safety protocols and company policy.
  • May be required to climb ladders, stoop, kneel, or crouch during inspections, maintenance walk-throughs, or emergency response situations.
  • Regular exposure to facility operations including noise, dust, temperature fluctuations, and industrial equipment.
  • Occasional off-hours or weekend work required for emergency facility responses or projects as needed
  • Requires frequent use of a computer and other standard office equipment for documentation, communication, and coordination tasks.

Background Check
This position will require successfully completing a post-offer background check. Qualified candidates with a criminal history will be considered and are not automatically disqualified, consistent with federal and state law.
EEO and ITAR/EAR Work Authorization Disclosure
Red Cat Holdings provides equal employment opportunities (EEO) to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This position requires direct or indirect access to hardware, software, technology or technical data controlled under the International Traffic in Arms Regulations (ITAR) and the Export Administration Regulations (EAR). Successful candidates for positions subject to ITAR/EAR restrictions must provide proof of U.S. Citizenship or Permanent Residence and must not require sponsorship for export-restricted work authorization.
E-Verify
The company participates E-Verify ensure eligibility for employment and compliance with Right to Work rules.
Compensation: Base pay, plus generous annual equity package and potential bonuses.

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