Top Tech Jobs & Startup Jobs in NYC, NY

Design, build, deploy, retrain, and monitor production machine learning models and components. Develop scalable ML infrastructure, data pipelines, cloud architectures, and distributed systems using Python and related technologies. Collaborate with Product and Data Science teams, automate testing and deployment, apply CI/CD practices, and ensure model governance, security, responsible AI, and explainability across enterprise platforms.

Leads engineering teams and portfolios delivering regulatory risk-management solutions using full-stack, distributed, cloud-native, and AI-enabled technologies. Designs architectures, builds reliable high-performance systems, defines platform roadmaps, mentors engineers, drives technology strategy, and establishes engineering standards. Collaborates with product leaders, architects, and cross-functional partners while leveraging AWS and other cloud platforms, microservices, databases, containers, APIs, observability, CI/CD, and modern development tools.

Supports Capital One’s broker-dealer compliance program by reviewing conflicts of interest, outside business activities, private securities transactions, gifts and entertainment, marketing materials, public appearances, and branch offices. Maintains supervisory designations and regulatory filings, conducts compliance inspections, updates procedures and risk assessments, manages issues, and provides advisory support to internal business clients.

Build and lead full-stack software engineering projects using cloud-based, distributed microservices and full-stack systems. Provide technical leadership across Agile teams, mentor engineers, establish coding standards, and partner with product managers and architects. Develop APIs, reusable frameworks, and scalable solutions using multiple programming languages, databases, container orchestration, and AWS services. Improve system performance, reduce technical debt, evaluate emerging technologies, and support regulatory business needs.

Architect, build, and deploy enterprise-scale generative AI and autonomous agent systems for HR technology. Lead multi-agent workflows, full-stack cloud applications, distributed microservices, and technical initiatives while ensuring security, governance, compliance, and operational excellence. Partner with product managers, architects, and risk teams; establish engineering standards; mentor developers; evaluate emerging technologies; and reduce technical debt. The role requires expertise in programming, databases, APIs, cloud platforms, CI/CD, infrastructure as code, RAG, vector search, and LangChain or LangGraph.

Leads complex full-stack engineering initiatives, technical projects, and developer teams. Designs and implements large-scale distributed, microservices, and cloud-native systems using modern programming languages, databases, containers, and cloud platforms. Provides architectural leadership, shapes platform roadmaps, establishes engineering standards, mentors engineers, drives reliability and observability practices, and collaborates with product and architecture leaders to deliver secure, high-performance solutions.

Own analytics engineering and the data transformation layer by designing data models, warehouses, cubes, semantic layers, and governance frameworks. Improve data quality, observability, metadata, self-service analytics, dashboards, and reporting platforms. Analyze large datasets, optimize queries, conduct testing and code reviews, support modernization initiatives, and collaborate across teams to deliver trusted metrics and insights.

Develop and deploy foundational AI systems, including LLM inference, foundation model training, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize AI systems for cost, latency, throughput, scalability, and hardware utilization. Architect multi-model orchestration pipelines, establish technical standards and governance, lead design reviews, contribute to long-term AI roadmaps, and mentor senior AI engineering staff.

Design, develop, deploy, and support foundational AI systems, including large language model inference, foundation model training, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize AI systems for scalability, cost, latency, throughput, and hardware utilization. Own complex system architectures, define reliability objectives, lead technical reviews, ensure security and compliance, and mentor engineering colleagues.

Leads software engineering projects and developer teams building distributed microservices, full-stack systems, and cloud-based solutions for Capital One Travel. Responsibilities include architectural design, technical leadership, platform strategy, refactoring, performance optimization, regulatory support, mentoring, and collaboration with product managers and engineering teams. The role uses Java, Scala, AWS, modern databases, container orchestration, APIs, CI/CD, infrastructure as code, and observability practices.