Top Tech Jobs & Startup Jobs in NYC, NY

Designs, develops, deploys, and supports production AI systems, including foundation models, LLM inference, agentic workflows, guardrails, evaluation, and observability. Owns complex AI architecture, reliability objectives, governance, and optimization for cost, latency, throughput, and hardware utilization. Partners across engineering, research, product, and program teams; leads technical reviews; contributes to long-term platform strategy; and mentors senior technical associates.

Designs, develops, deploys, and supports foundational AI systems, including LLM inference, agentic workflows, vector search, guardrails, evaluation, and multi-model orchestration. Optimizes AI systems for cost, latency, throughput, scalability, and hardware utilization. Leads governance reviews and design councils, contributes to technical roadmaps, establishes responsible AI standards, and mentors senior engineering leaders.

Lead product management for Recoveries and Discover integration initiatives. Define customer segmentation and decisioning solutions, prioritize roadmaps, translate business epics into features and user stories, establish acceptance criteria, and direct technology team priorities. Partner with business, technology, design, data science, operations, and other stakeholders in an agile environment to deliver customer-facing digital products and business-critical platform enhancements.

Leads enterprise compliance testing across a financial institution, managing multi-tiered teams, testing methodologies, calendars, data scripts, reporting, and audit responses. Partners with compliance, data, technology, and business teams to improve testing through innovation, communicate significant findings to senior leadership, and ensure timely, accurate execution. The role requires substantial financial services compliance, risk, audit, people leadership, regulatory, and analytical experience.

Design, develop, deploy, and support large-scale generative AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, and observability. Optimize AI systems for cost, latency, throughput, scalability, and hardware utilization. Establish governance and engineering standards, lead design reviews, contribute to platform strategy, and mentor senior AI engineers.

Build, deploy, scale, and monitor production machine learning models and infrastructure. Develop optimized data pipelines, cloud-based architectures, automated testing, and CI/CD workflows. Collaborate with product, data science, and Agile teams while applying responsible AI, model governance, and software engineering best practices. The role requires expertise in machine learning frameworks, distributed systems, cloud operations, Kubernetes, and production model deployment.

Executes risk-based compliance reviews to independently validate business adherence to laws, regulations, and internal frameworks. The role tests regulatory requirements, data, automation, and controls; analyzes data; manages review schedules and documentation; supports audits and exams; and collaborates with compliance advisors, business teams, and analytics professionals to improve testing approaches. Strong judgment, problem-solving, communication, and professional skepticism are required.

Develop and operate large-scale generative AI systems, including foundation models, LLM inference, agentic workflows, guardrails, model evaluation, vector search, memory, governance, and observability. Lead architecture and optimization for cost, latency, throughput, reliability, and hardware utilization. Define AI service objectives, ensure security and compliance, guide technical roadmaps, and mentor engineering teams.

Build and implement machine learning models for personal loan acquisition, including customer selection, campaign optimization, underwriting, pricing, and verification. Partner with data scientists, engineers, and product managers; analyze large-scale numeric and textual datasets using Python, Spark, AWS, and related tools; validate and backtest models; and translate statistical insights into customer-focused business outcomes.

Design, develop, deploy, and support large-scale AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize model performance, scalability, latency, throughput, hardware utilization, and cost. Lead technical reviews and governance, define AI platform roadmaps, integrate heterogeneous AI systems, and mentor senior engineering talent.