Top Tech Jobs & Startup Jobs in NYC, NY

Leads Client360 product strategy, discovery, roadmap, backlog, metrics, and lifecycle execution. Drives business initiatives, process improvement, operational efficiency, stakeholder alignment, and cross-functional delivery across banking functions. Uses analytics, machine learning, and AI to generate insights, while guiding launches, managing risk, improving platforms, and mentoring junior team members.

Lead and develop a team of Financial Advisors, recruit talent, drive cross-partner integration, promote customer-focused culture, manage day-to-day supervisory and operational responsibilities, and enforce risk and control standards while leveraging technology to enhance client solutions.

Leads enterprise PCI DSS assessments and regulatory compliance activities within JPMorganChase’s Cybersecurity Technology Controls team. Manages concurrent assessments, validates scope and documentation, coordinates with Qualified Security Assessors and control owners, identifies compliance gaps, guides remediation and compensating controls, and reports risk findings and metrics to stakeholders. Applies technology risk, audit, regulatory, and control expertise while using automation and artificial intelligence to improve assessment efficiency and quality.

Owns end-to-end delivery and optimization of local advisor, office, and branch website initiatives for Chase Wealth Management. Coordinates Marketing, Design, Analytics, Product, Technology, Legal, vendors, and agencies to develop compliant, trackable digital experiences. Manages requirements, creative development, timelines, approvals, launch readiness, issue resolution, stakeholder communications, and continuous improvement to support client acquisition and engagement.

Leads second-line compliance and operational risk oversight for Kinexys and CIB Payments. Assesses risks associated with new products, technologies, vendors, client onboarding, blockchain, and digital assets. Develops risk frameworks, monitors regulatory changes, supports controls and process improvements, and collaborates with Compliance, Legal, Product, Audit, Finance, and other stakeholders to deliver compliant business outcomes.

Supports strategic priorities across Wealth Management Technology by coordinating initiatives, preparing executive presentations and reports, managing leadership communications, synthesizing business data, and improving operational processes. Partners with Product, Finance, Data, Design, and business leaders to track portfolio progress, align stakeholders, and deliver workstreams from initiation through completion.

Leads enterprise product solutions and integration initiatives from strategy through delivery. Manages client implementations, onboarding, stakeholder relationships, cross-functional collaboration, product requirements, integration needs, and user stories. Supports go-to-market strategy and product positioning while driving innovation for wealth and asset management clients. Requires strong financial services expertise, enterprise product or program management experience, and the ability to lead complex engagements and implementations.

Lead strategy and execution for machine learning-powered personalization and next-best-action products across digital and service channels. Translate research, analytics, and customer feedback into roadmaps, requirements, user stories, experiments, and measurable outcomes. Collaborate with data scientists, ML engineers, channel teams, and stakeholders to deliver recommendation, assistant, and context-driven data products. Support model lifecycle infrastructure, API and event-driven architectures, responsible data practices, privacy, consent, fairness, and backlog execution.

Leads machine learning-powered personalization and next-best-action product initiatives across digital and service channels. Translates user research, analytics, and customer feedback into product roadmaps, requirements, epics, user stories, experiments, and backlog priorities. Partners with product, design, data science, engineering, channel, and business teams to deliver AI products, data platforms, and model lifecycle capabilities while supporting privacy, consent, fairness, reliability, and measurable customer outcomes.

Build and operate scalable MLOps infrastructure for recommendation and personalization systems. Responsibilities include distributed GPU training pipelines, real-time and batch inference, LLM quantization and serving with Ray and vLLM, vector database optimization, monitoring, observability, and production validation. The role partners with data scientists, product, architecture, and engineering teams to deliver high-throughput, low-latency machine learning applications on AWS.