Top Tech Jobs & Startup Jobs in NYC, NY

Lead product analytics for Enterprise Data products, validating analytical tools, assessing methodology risks, researching emerging practices, and translating complex data into actionable insights. Manage validation projects, communicate findings through reports and presentations, and coach junior staff. The role requires advanced data analysis, statistical or econometric modeling, predictive analytics, large-dataset analysis, data governance, and people leadership.

Leads engineering teams and portfolios delivering cloud-native, distributed, full-stack systems for risk management and regulatory needs. Provides technical leadership across architecture, platform roadmaps, reliability, performance, observability, and shared services. Builds AI-powered solutions using modern programming languages, databases, containers, cloud platforms, APIs, CI/CD, and infrastructure as code. Mentors engineers, drives technology strategy, and influences enterprise-wide standards.

Design, build, and operate scalable cloud data platforms, pipelines, and applications. Collaborate with Agile teams, product managers, engineers, analysts, and data scientists while applying Python, Spark, SQL, Databricks, Snowflake, relational and NoSQL databases. Establish reusable engineering patterns, data security controls, and resilient architectures. Mentor data professionals, communicate technical concepts to stakeholders, and deliver user-centric data solutions with minimal supervision.

Design, develop, deploy, and optimize large-scale AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, orchestration pipelines, and observability. Lead cost-performance governance, technical design reviews, AI standards, roadmap development, and mentorship while improving model scalability, latency, throughput, hardware utilization, and inference costs.

Leads technical vision and architecture for Card Tech while remaining hands-on in software development. Modernizes monoliths into microservices and event-driven platforms, establishes API and design standards, ensures scalable and secure implementations, and mentors engineering teams. The role requires expertise in cloud computing, data architecture, distributed systems, enterprise architecture, and AI-native development, along with leadership of cross-divisional initiatives and talent recruitment.

Leads technical vision and architecture for high-volume payment systems. Designs scalable, resilient distributed platforms; modernizes monoliths into microservices and event-driven architectures; establishes API and engineering standards; ensures performance, operability, and implementation quality; mentors engineers; contributes hands-on code and technical guidance; and leads cross-domain architectural initiatives across the organization.

Leads full-stack engineering projects and developer teams building large-scale, distributed, cloud-native systems. Designs architectures, implements reliable microservices and APIs, shapes platform roadmaps, and partners with product and architecture leaders. Uses modern programming languages, databases, container orchestration, cloud platforms, CI/CD, observability, and automated testing. Provides technical mentorship, establishes engineering standards, leads design reviews, and drives enterprise technology strategy and cross-functional initiatives.

Leads full-stack engineering teams and technology portfolios within Risk Tech. Responsibilities include mentoring engineering leaders, directing large-scale cloud-native and distributed system development, setting technical roadmaps, managing Agile programs, partnering with product and architecture leaders, and aligning engineering execution with enterprise goals. The role involves Java, Python, Go, JavaScript, AWS, Kubernetes, databases, AI-powered solutions, and occasional coding or code evaluation.

Leads cybersecurity governance, capability maturity, risk assessments, and enterprise risk-reduction initiatives. Manages and mentors cybersecurity professionals, advises on security tools and platforms, develops risk and threat classification frameworks, and coordinates continuous improvement programs. The role evaluates controls, capabilities, tooling, threats, and vulnerabilities; communicates remediation recommendations to leadership; supports cybersecurity metrics and dashboards; and drives consistent control design, testing, and reporting across cyber programs.

Design, develop, deploy, and support scalable generative AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize model performance, cost, latency, throughput, and hardware utilization across distributed cloud platforms. Own AI system architecture and reliability objectives, lead technical reviews, ensure security and compliance, contribute to long-term platform roadmaps, and mentor engineering staff.