Fraud Hub Lead Engineer

hackajob is collaborating with BNY to connect them with exceptional professionals for this role. Corporate Engineering – Fraud Hub Lead Engineer At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide. Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what is all about. Join us and be part of something extraordinary. We’re seeking a future team member for the role of Fraud Hub Lead Engineer to join our Corporate Engineering team. This role can be in NYC, NY or Pittsburgh, PA or Lake Mary, FL Role Overview We are seeking an experienced Fraud Hub Lead Engineer to lead the global Engineering strategy and execution for BNY’s Fraud Hub. This role serves as the firmwide engineering authority for Fraud detection, prevention, and response platforms, with responsibility for defining architecture, driving AI‑first solutions, and delivering secure, resilient, and scalable systems. As part of Corporate Engineering, you will lead the engineering organization responsible for the platforms that protect identity and payment methods across wires, cheques, cards, and emerging payment channels. This is a senior leadership role for a hands‑on, technically credible engineering leader who combines deep Fraud domain expertise with modern software, data, and AI engineering capabilities. Key Responsibilities Enterprise Fraud Engineering Leadership Define and execute the global engineering strategy for BNY’s Fraud Hub, acting as the single engineering owner for Fraud platforms, standards, and delivery. Build, lead, and inspire a high‑performing global engineering organization with strong technical depth, clear ownership, and a relentless focus on quality and outcomes. Establish engineering standards for availability, resiliency, security, model risk management, and operational excellence across all Fraud technology. Platform, Architecture, and AI Ownership Own the end‑to‑end architecture, build, and operation of scalable, real‑time Fraud detection and decisioning platforms. Design and operate streaming, event‑driven systems for real‑time Fraud detection, monitoring, and response across high‑volume payment and transaction flows. Integrate emerging AI‑driven systems for anomaly detection, behavior analysis, alert prioritization, investigation, and remediation. Solutions must include biometrics, video and voice analytics. Develop retrospective and “after‑event” analytics capabilities to continuously improve models, controls, and defenses against emerging Fraud threats. Anticipate new Fraud vectors and proactively evolve platforms, data, and AI capabilities using a 360 mindset to stay ahead of the threat landscape. Delivery, Operations, and Performance Provide full lifecycle ownership for Fraud platforms, including build, run, resiliency, incident response, and continuous improvement. Establish, track, and report KPIs and OKRs including uptime, MTTR, change success rate, SLA adherence, throughput, and operational risk indicators. Champion modern DevSecOps and MLOps practices, ensuring safe, repeatable, and auditable deployment of software and AI into production. Enterprise Partnership and Influence Partner closely with Risk, Compliance, Cyber, Legal, Operations, and Product teams to translate regulatory and risk requirements into actionable engineering outcomes. Serve as a trusted engineering leader to senior executives and stakeholders, influencing investment, prioritization, and strategic direction. Provide a firmwide hub of Fraud engineering expertise, intelligence, and best practices, enabling consistent, high‑quality outcomes across the enterprise. Required Qualifications & Experience 10+ years of software engineering experience, with at least 5 years delivering Fraud, Financial Crime, or large‑scale risk analytics platforms. Proven experience building and deploying AI/ML‑driven solutions for Fraud detection, anomaly detection, or real‑time risk decisioning. Demonstrated success leading and scaling global e