Software Engineer, Trustus

Accountabilities:

• • Build and operate large-scale backend systems that detect fraudulent activity, using rules, productionized machine learning models, APIs, and high-volume data pipelines.
  • Investigate end-to-end systems to understand how fraudulent listings are created, where vulnerabilities exist, and how bad actors can be detected or prevented.
  • Partner with machine learning engineers, data scientists, product managers, designers, research teams, and customer service operations to identify, refine, prioritize, and deliver high-impact fraud prevention initiatives.
  • Develop tooling and automation that enables operations teams to investigate and mitigate fraudulent activity more efficiently and consistently.
  • Design and implement user challenges and verification mechanisms that prevent fraudulent listings while minimizing disruption to legitimate users.
  • Build and improve data pipelines and supporting infrastructure for machine learning and fraud detection systems.
  • Contribute to initiatives such as location verification, automated fraud investigations, operational tooling, and large-scale fraud mitigation.
  • Write high-performance, production-quality code and contribute to scalable architectural solutions for complex trust and risk challenges.
  • Communicate technical concepts, risks, and proposed solutions effectively with both technical and non-technical stakeholders, including operations and legal partners.
  • Continuously identify opportunities where engineering solutions can meaningfully reduce fraud, financial losses, and negative customer experiences.

  Requirements:

  • Have 3+ years of professional software engineering experience building and operating systems at scale; relevant master's or PhD experience may also be considered.
  • Demonstrate a strong passion for building user-facing products, robust backend services, or other high-scale software systems.
  • Have professional experience with one or more relevant programming languages or frameworks, such as Ruby/Ruby on Rails, Java, JavaScript, Python, or Scala.
  • Be capable of writing efficient, reliable, maintainable, production-quality code.
  • Understand architectural patterns for large-scale web applications, including well-designed APIs, high-volume data pipelines, scalable services, and efficient algorithms.
  • Be comfortable working across disciplines and collaborating closely with product, design, data science, machine learning, research, and operations teams.
  • Demonstrate strong communication skills and the ability to translate technical concepts into clear discussions with non-technical stakeholders.
  • Bring strong curiosity and analytical problem-solving skills, particularly when investigating complex systems and identifying sources of fraud or abuse.
  • Experience in Trust & Safety, fraud prevention, risk management, or a related domain is a plus.
  • Be comfortable operating in an environment where priorities evolve and where engineers are expected to take ownership of meaningful, ambiguous problems.

  Benefits:

  • Base salary: $162,000–$186,000 USD annually.
  • Potential eligibility for bonus and equity compensation.
  • Comprehensive employee benefits.
  • Employee travel credits.
  • US-remote eligible working arrangement, with occasional office work or team offsites as agreed with your manager.
  • Opportunity to work on technically challenging, high-scale systems with direct impact on user safety and trust.
  • Collaborative environment with engineers, data scientists, machine learning specialists, product leaders, designers, and operations teams.
  • Inclusive workplace committed to equal opportunity, diversity, belonging, and accessible hiring practices.