Top Tech Jobs & Startup Jobs in NYC, NY

Leads major technology projects and engineering teams developing large-scale, distributed, cloud-native systems. Responsibilities include full-stack design and implementation, technical architecture, platform roadmap development, cloud solution delivery, reliability and performance optimization, regulatory technology support, mentoring engineers, and establishing technical standards across teams. The role uses modern programming languages, databases, container orchestration, AWS services, observability practices, and AI-enabled development tools.

Executes risk-based compliance reviews to independently validate business adherence to laws, regulations, and control frameworks. Tests business processes, data, automation, and regulatory controls; analyzes data; documents results; manages review schedules; supports audits and examinations; and partners with Compliance Advisors and business teams to improve testing approaches. The role requires strong judgment, skepticism, communication, and the ability to explain technical findings to nontechnical stakeholders.

Lead enterprise AI engineering strategy and teams building scalable agentic AI platforms. Oversee foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, observability, and AI operations. Drive build-versus-buy decisions, optimization, responsible AI practices, multi-year technical roadmaps, and cross-functional alignment while developing senior engineering talent and supporting hundreds of production use cases.

Design, develop, deploy, and support foundational AI systems, including large language model inference, agents, similarity search, guardrails, evaluation, governance, and observability. Optimize model training and inference for cost, latency, throughput, scalability, and hardware utilization. Own complex AI architecture, define reliability objectives, lead technical reviews, ensure security and compliance, and mentor senior technical staff.

Design, develop, deploy, and optimize foundational AI systems, including LLM inference, foundation model training, agentic workflows, vector search, guardrails, evaluation, and observability. Lead multi-model orchestration, cost-performance governance, architecture reviews, technical roadmaps, and responsible AI standards. Mentor senior technical staff and collaborate with engineers, scientists, product managers, and program managers to deliver scalable AI products.

Provides legal and regulatory counsel to enterprise technology teams developing and governing AI-driven, cloud, and emerging technology platforms. Advises on technology risk, cybersecurity and privacy laws, regulatory examinations, audits, disclosures, strategic technology contracts, and third-party vendor relationships. Partners with technology, product, design, risk, compliance, regulators, and business leaders to identify risks and enable legally supported innovation.

Design, develop, deploy, and support foundational AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, and observability. Optimize large-scale AI systems for cost, latency, throughput, reliability, and hardware utilization. Own complex AI architecture, define reliability objectives, support governance and compliance, lead technical reviews, contribute to long-term AI roadmaps, and mentor senior technical staff.

Performs data analysis, business intelligence, data management, and data quality work for Emerging Payments and AirKey. Builds data solutions, dashboards, metrics, and self-service tools; analyzes complex structured and unstructured data; partners with business and technology teams; and supports metadata, lineage, data governance, security, access controls, and data quality monitoring using Python, R, Spark, SQL, Snowflake, and AWS.

Lead Capital One’s Recoveries Modernization product initiative by migrating downstream applications to modern streaming data assets, decommissioning legacy customer and account systems, defining API contracts and data products, prioritizing the post-MVP roadmap, and implementing automated data controls. The role requires cross-functional leadership across technology, operations, business analysis, risk, and downstream clients, with a hybrid work arrangement.

Leads enterprise AI enablement product strategy and adoption across Capital One. Owns internal AI products, developer platforms, workflows, responsible AI practices, evaluation pipelines, change management, and multi-year roadmaps. Partners cross-functionally with technology, design, risk, finance, legal, and business leaders to improve productivity, reduce operational toil, and deliver measurable outcomes through AI-native product development.