Software Developer, Ops Platform and Fraud Investigations

About the role

This position invites you to join a team dedicated to transforming how critical operational work is executed by replacing manual, repetitive tasks with automated, AI-driven systems. You will be responsible for designing and building internal platforms that empower teams across the organization to handle fraud, account management, and financial crimes with greater speed and accuracy. The role focuses on creating robust infrastructure that supports high-stakes investigations while improving the reliability and scalability of day-to-day operations. You will work closely with cross-functional partners to understand complex workflows and translate them into resilient software solutions. The position emphasizes ownership of the full lifecycle of platform features, from initial design and implementation to deployment and ongoing optimization. You will play a key role in ensuring that the systems you build are secure, performant, and aligned with regulatory requirements. By leveraging modern distributed architectures and AI technologies, you will help reduce friction in operational processes and enable teams to make faster, data-informed decisions.

Key facts

What you'll do

• Architect and build systems that support operational workflows across various product lines, ensuring scalability and maintainability.
• Develop tools to process large datasets, providing actionable insights that assist in fraud investigations and risk assessments.
• Partner with data scientists and machine learning engineers to automate manual review processes, reducing cycle times and human error.
• Create AI-based applications that increase the speed and precision of operational tasks, improving throughput and consistency.
• Improve system architecture to accelerate development cycles, reduce technical debt, and support new product launches efficiently.
• Design and implement APIs and services that enable seamless communication between internal platforms and external data sources.
• Collaborate with product managers and operations leads to define technical requirements and translate business needs into robust software solutions.
• Monitor system performance in production, identifying bottlenecks and driving optimizations to enhance reliability and user experience.
• Build dashboards and analytical tools that provide visibility into operational metrics, helping stakeholders make informed decisions.
• Contribute to the development of automation frameworks that standardize how repetitive tasks are handled across the organization.
• Write clean, well-documented code that adheres to best practices and supports long-term maintainability.
• Participate in code reviews and technical discussions to uphold high engineering standards across the team.
• Work within an agile development process, delivering incremental improvements and responding quickly to changing priorities.
• Support the deployment and maintenance of systems in production, collaborating with site reliability and infrastructure teams as needed.

Requirements

• Proven experience designing and scaling distributed systems with a focus on performance, reliability, and operational resilience.
• Experience building and maintaining applications that integrate large language models or similar AI systems in production environments.
• Ability to structure systems that manage model behavior, ensuring consistent, reliable, and secure outputs across different use cases.
• Experience working with large-scale data pipelines to extract insights from complex, multi-source information sets.
• Ability to convert business requirements into technical solutions with clear milestones, realistic timelines, and measurable outcomes.
• Strong understanding of software development lifecycle practices, including testing, deployment, and monitoring in production.
• Demonstrated ability to work independently and collaboratively in a fast-paced, dynamic operational environment.
• Familiarity with security and compliance considerations relevant to financial services and fraud detection systems.

Skills & tools

• Distributed systems architecture
• Large language models (LLM) and AI integration
• Large-scale data pipelines
• Production-grade machine learning systems
• Experience with cloud platforms and infrastructure-as-code practices
• Proficiency in at least one modern programming language relevant to backend services
• Knowledge of data storage technologies, including databases and streaming platforms
• Understanding of monitoring, logging, and observability tools

Practical notes

• Compensation includes base pay, bonus opportunities, and equity.
• Benefits include supplemental health insurance, mental health support, a lifestyle wallet for wellness/childcare/learning, and a monthly commuter stipend.
• Time off includes paid time off, sick leave, parental leave, and volunteer time.
• Candidates requiring accommodations for the interview process may use the Applicant Accommodation Form.
• Robinhood utilizes AI tools during the recruitment process, though all final hiring decisions are made by human teams.
• This role is based in Toronto, Canada, with a requirement to work in-office a minimum of 3 days per week.
• The position is full-time and eligible for standard benefits and compensation packages as described.
• Applicants should be available to start within a reasonable timeframe as discussed during the hiring process.
• No sponsorship is available for this role at this time.