Senior Staff Risk Engineer

Overview

Intuit is a global technology platform that helps customers and communities overcome financial challenges. Serving over 50 million customers worldwide, Intuit Fintech seeks a Senior Staff Software Engineer to lead the technology vision and architecture of the Fintech Risk Platform. This role operates at the intersection of risk intelligence, large-scale distributed systems, AI/GenAI, and financial infrastructure.

Responsibilities

• Define and drive the multi-year technical vision and architecture for the Fintech Risk Platform, aligning with Intuit’s broader financial ecosystem strategy.

• Architect systems capable of supporting $1T+ annual money movement with industry-leading availability, latency, and security guarantees.

• Establish a forward-looking roadmap for risk intelligence, leveraging AI/ML and GenAI to evolve from reactive fraud detection to proactive risk prevention and autonomous decisioning.

• Balance risk mitigation, customer experience, and growth, ensuring optimal trade-offs between fraud prevention, false positives, and customer friction.

• Lead the design of end-to-end risk decisioning systems, spanning transaction processing, identity verification, fraud detection, compliance, and dispute handling.

• Drive cross-functional architecture across payments, ledgers, identity, analytics, and customer platforms to ensure cohesive and scalable solutions.

• Establish real-time and batch risk pipelines that unify signals across the ecosystem to deliver consistent, low-latency decisions.

• Ensure systems are auditable, explainable, and compliant with evolving financial regulations.

• Design and oversee platforms that operate at extreme scale, handling billions of transactions with sub-second risk decisions.

• Lead the development of resilient, fault-tolerant distributed systems with strong consistency guarantees for financial correctness.

• Drive innovations in risk scoring, anomaly detection, and behavioral modeling to significantly reduce fraud and abuse.

• Optimize systems to reduce fraud loss rate, minimize customer friction, and increase approval rates for good transactions.

• Champion the integration of advanced ML models and GenAI into risk workflows, including:

  • Fraud detection and classification
  • Identity risk assessment
  • Adaptive policy generation
  • Explainable AI for compliance and auditability

• Define best practices for model lifecycle management, experimentation, and real-time inference at scale.

• Partner with data science teams to translate models into production-grade, scalable systems.

• Own and influence key business metrics, including:

  • Fraud loss rate reduction
  • False positive rate / customer friction
  • Customer churn due to risk decisions
  • Approval rates and revenue protection

• Establish measurement frameworks, experimentation strategies (A/B testing), and executive dashboards to guide decision-making.

• Continuously refine systems to maximize trust while enabling growth.

• Act as a technical authority across multiple organizations, influencing architecture, design standards, and engineering practices.

• Lead and mentor senior and staff engineers, raising the overall technical bar across the organization.

• Drive engineering excellence in scalability, reliability, observability, and security.

• Partner with executives and cross-functional leaders to align technology investments with business priorities.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, or equivalent experience.

• 12+ years of experience building and scaling complex distributed systems, with a strong track record of technical leadership.

• Proven experience architecting large-scale financial systems, payment platforms, or risk/fraud systems.

• Deep expertise in backend systems (Java, Spring Boot, or equivalent), frontend technologies (React or modern frameworks), cloud platforms (AWS preferred), and distributed architectures.

• Strong experience with AI/ML systems in production, including real-time decisioning and model integration.

• Demonstrated ability to design systems operating at extreme scale (billions of transactions, low-latency decisioning).

• Expertise in risk analytics, fraud detection strategies, and compliance requirements in Fintech.

• Proficiency in data technologies (Python, SQL, data pipelines, streaming frameworks).

• Exceptional ability to drive alignment across engineering, product, data science, and business stakeholders.

• Strong business acumen with the ability to connect technical decisions to financial outcomes and customer impact.

Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The Expected Base Pay Range For This Position Is Mountain View $220,500 - $298,500 New York $220,500- $298,000