Top Tech Jobs & Startup Jobs in NYC, NY

Leads Partner Experiences product design within Capital One’s Global Payment Network. Combines product design expertise and people leadership to shape product strategy, solve complex customer and business problems, align product, technology, and business stakeholders, and develop high-performing designers. Responsibilities include human-centered research and design, prototyping, design systems, portfolio direction, stakeholder communication, and team culture development.

Lead product strategy and development for business data products, including enterprise business identity, profiling, relationship matching, and customer data architecture. Enable associates across operations, call centers, and digital channels with comprehensive business-client relationship views. Prioritize servicing experiences for active and complex business customers while leading cross-functional teams, translating strategy into technology solutions, and driving customer-focused transformation.

Conduct technology and cybersecurity audits for a global payment network, including risk assessments, control testing, cloud infrastructure, application controls, third-party management, and technology implementations. Document audit work, communicate risks and recommendations, track remediation actions, use data analytics, and collaborate with business partners and Audit teams.

Leads a team of data stewards and oversees Customer Information data assets throughout their lifecycle. Ensures policy compliance, data quality, regulatory alignment, and effective stewardship. Develops and improves processes, creates performance metrics, resolves data issues, partners with Product, Technology, enterprise tooling, and risk governance teams, and drives operational efficiency. Provides subject matter expertise while coaching team members and managing cross-functional relationships.

Leads enterprise-wide omnichannel personalization strategy across websites, push notifications, and SMS. Owns the roadmap for AI/ML-driven personalization models, partners with data science and ML engineering teams, drives experimentation platforms, and delivers personalized customer experiences and measurable business outcomes. Provides transformational product leadership while balancing customer needs, business value, technology, risk, and cross-functional alignment.

Develop machine learning models for business card credit underwriting across the full lifecycle, from design and training through validation and implementation. Collaborate with data scientists, engineers, product managers, and business stakeholders to develop scalable solutions using large datasets and cloud technologies. Translate complex analysis into business outcomes and apply statistical methods including classification, clustering, sentiment analysis, time series, and deep learning.

Leads product management for consumer digital experiences, translating customer needs and business strategy into innovative, technology-driven products. Drives cross-functional alignment, solves complex product problems, manages product risks, and delivers scalable experiences through data, AI, and front-end engineering. Requires a quantitative, business, or marketing degree, or a bachelor’s degree with four years of product management experience.

Build and scale enterprise machine learning platforms and production ML systems. Develop models, data pipelines, distributed training workflows, Kubernetes operators, SDKs, and developer tooling using Python and cloud technologies. Deploy, monitor, retrain, and govern ML models while applying CI/CD, testing, security, and responsible AI practices. Collaborate with Product, Data Science, and Agile engineering teams, and contribute to open-source Kubeflow.

Leads content design and UX writing for digital product experiences, creating accessible microcopy, content systems, guidelines, taxonomies, and governance models. Partners with product, technology, business, and research teams to shape customer-centered solutions and product strategy. Directs design projects, mentors junior designers, presents strategic recommendations, and contributes to the maturity of the design practice.

Design, develop, deploy, and support foundational AI systems, including LLM inference, multimodal safety guardrails, agents, similarity search, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, reliability, and hardware utilization. Lead architecture and technical reviews, define AI reliability objectives, ensure security and compliance, and mentor engineering staff.