Senior Software Developer, Ops Platform and Fraud Investigations

Robinhood Robinhood · Fintech · Toronto, ON · ENG Executive Office

Robinhood is seeking a Senior Software Developer for their Ops Platform and Fraud Investigations team. This role involves designing and building internal platforms that replace manual processes with AI-driven systems to support areas like Fraud Operations and Account Operations. The developer will work with large datasets and signals to create tooling for fraud detection and investigation, collaborate with data scientists and ML engineers to automate manual processes, and design/develop AI-based applications to improve operational speed and accuracy. The focus is on improving system reliability, reducing operational effort, and increasing the speed of new feature support.

What you'd actually do

  1. You will define technical direction and make architectural decisions for systems that support operational workflows across multiple product lines
  2. You will build tools that process large datasets and generate insights to support fraud investigation and decision-making
  3. You will work with data scientists and machine learning engineers to implement systems that automate manual review processes
  4. You will design and develop AI-based applications that improve the speed and accuracy of operational tasks
  5. You will contribute to system improvements that increase development velocity and reduce time required to launch new capabilities

Skills

Required

  • experience designing and scaling distributed systems with a focus on reliability and performance
  • experience building and operating applications that use large language models or similar AI systems in production environments
  • understand how to structure systems that manage model behavior and ensure consistent, reliable outputs
  • experience working with large-scale data pipelines and extracting meaningful insights from complex datasets
  • translate business processes into technical solutions with clear milestones and measurable outcomes

What the JD emphasized

  • AI-driven systems
  • fraud detection and investigation workflows
  • automate manual review processes
  • AI-based applications
  • large language models or similar AI systems in production environments
  • model behavior

Other signals

  • AI-driven systems
  • fraud detection and investigation workflows
  • automate manual review processes
  • AI-based applications