Make your impact within a rapidly growing Fintech Company

Join BILL's Risk Engineering organization as a Senior Staff Software Engineer and take on some of the most consequential technical challenges in fintech. Our Risk Engineering team builds the platforms that protect hundreds of thousands of SMBs from financial harm, owning the risk decisioning infrastructure, onboarding compliance systems, access control frameworks, and real-time signal processing pipelines that operate across payment, lending, and spend products. The team sits at the intersection of security engineering and financial risk, where the decisions you build into software directly affect whether a small business can trust BILL with their money.

In this role, you will drive the technical vision and delivery of risk platform services with a security-by-default, platform-first mindset, from real-time decisioning engines and onboarding compliance workflows to privileged access controls and cloud security infrastructure in AWS. You will partner closely with Product, Data Scientists, Compliance, Risk Strategy and Infrastructure teams to turn complex fraud, regulatory, and identity signals into reliable, low-latency systems. A key part of this role is elevating engineering excellence by embedding AI-assisted workflows into design, testing, and development cycles to accelerate team velocity and code quality. This is hands-on technical leadership: you will not only define strategy but deliver production systems that raise the platform and security bar across the enterprise.

Responsibilities:

• Architect and own core risk and onboarding platform services, including real-time decisioning engines, transaction monitoring pipelines, identity and workflow orchestration systems, and access eligibility controls that process high volumes of payments with strict latency, reliability, and accuracy requirements.
• Set the technical vision for cross-product onboarding and compliance platforms, establishing extensible patterns that support new customer types, products, and global geographies while meeting diverse regulatory requirements.
• Define and deliver a technical roadmap for risk and access control infrastructure, incorporating Zero Trust principles, role-based access controls, and privileged access management patterns into BILL's risk platform.
• Partner with AWS infrastructure and cloud architecture teams to design and implement security controls that enforce security-by-default across BILL's cloud environment, proactively identifying and remediating gaps in hygiene and configuration.
• Collaborate with data science teams to operationalize machine learning models for fraud detection and risk scoring, designing integration patterns that move models from research to production with appropriate observability, auditability, and controls.
• Define and champion standards for AI-assisted engineering, embedding tools like Claude into design reviews, testing, and debugging workflows to improve delivery speed and code quality across the organization.
• Lead end-to-end delivery of complex cross-functional risk and onboarding initiatives, coordinating across engineering, compliance, legal, and operations from requirements through production deployment.
• Mentor and elevate engineers on the risk team, investing in technical growth and raising the overall standard for system design, code quality, security thinking, and AI adoption.

We'd love to chat if you have:

• 12+ years of software engineering experience, with meaningful time spent building risk, fraud, identity, onboarding compliance, or security platform systems at scale in a fintech or financial services environment.
• Deep expertise designing and building distributed, high-availability, low-latency systems in Java or a comparable JVM language, with strong command of system design tradeoffs under real-world production constraints.
• Hands-on experience implementing access control systems, including RBAC, privileged access management, or authentication and authorization frameworks in large-scale SaaS or cloud-native environments.
• Experience deploying and securing applications in AWS, with working knowledge of cloud security controls, IAM policies, and infrastructure hardening practices.
• Demonstrated track record leading large technical initiatives across engineering, compliance, and executive audiences in ambiguous, high-growth environments.
• Experience leveraging AI tools to meaningfully improve engineering delivery speed, code quality, or team workflows at an individual or organizational level.
• Has shipped an AI-powered feature to production and owned its reliability/monitoring
• Applying AI in risk, fraud, or compliance contexts — model-assisted decisioning, anomaly detection, or human-in-the-loop review workflows

Desired Qualifications:

• Experience integrating machine learning models into production risk or fraud pipelines, including feature engineering, model serving infrastructure, and monitoring for model drift.
• Background working with real-time streaming architectures such as Kafka for risk signal processing or event-driven fraud detection systems, and familiarity with observability tooling such as Datadog or OpenTelemetry.
• Familiarity with financial compliance and regulatory frameworks relevant to payment, lending, or onboarding risk, including KYC/KYB, BSA/AML, or transaction monitoring.

Please note that this position is not eligible for visa sponsorship. Applicants must have authorization to work in the United States without requiring visa sponsorship now or in the future.