Top Tech Jobs & Startup Jobs in NYC, NY

Own end-to-end technical program delivery from inception through production. Coordinate engineering, product, finance, modeling, and business teams; define scope, sequencing, dependencies, metrics, and execution plans. Remove blockers, lead Agile rituals, report program health and risks, adapt priorities, and improve TPM practices, standards, and tooling. Translate complex technical concepts for stakeholders and influence across teams without direct authority.

Build and optimize high-performance platforms for simulated and live trading across financial markets and asset classes. Responsibilities include implementing trading and measurement applications, analyzing system performance, reviewing code, extending platforms, and supporting traders with portfolio orders. The role requires systems-level programming, market structure knowledge, and collaboration with quantitative modeling teams.

Develop sophisticated quantitative trading models using scientific methods, machine learning, statistical techniques, and large datasets. The researcher will create and test investment ideas, collaborate with engineers, follow current academic research, attend seminars and conferences, and share insights in statistics, machine learning, and data science.

Create branded visual assets for social media, websites, internal communications, digital campaigns, and print. Translate creative briefs into polished designs, maintain brand systems and asset libraries, iterate based on feedback, manage multiple projects, and explore AI-assisted design tools. Collaborate with marketing and communications stakeholders while ensuring visual consistency, accessibility to technical concepts, and alignment with campaign objectives.

Analyze quantitative modeling workflows to identify GPU acceleration opportunities, re-engineer pipelines for GPU parallelism, validate correctness and throughput, inform GPU infrastructure needs, and translate modeler requirements into technical specifications. The role requires expertise in modeling platforms, the full modeling lifecycle, Python scientific computing, and collaboration with quantitative modelers.

Own the architecture, reliability, operations, and roadmap of a large-scale Kubernetes platform across on-premise and cloud environments. Lead technical strategy, troubleshoot and monitor platform performance, build software components in Go, Java, or Python, and drive cloud-native, GitOps, infrastructure-as-code, and CI/CD improvements. Mentor engineers, establish technical standards, and balance strategic platform investments with business-critical trading, services, and data pipeline requirements.

Build and deploy production AI-powered systems across the firm. Responsibilities include designing agent-based workflows, integrating AI capabilities with APIs, MCP servers, data pipelines, and internal tools, and maintaining deployment, monitoring, observability, and operational infrastructure. The role requires autonomous problem scoping, architectural decision-making, collaboration with diverse teams, and practical experience building reliable software and agentic AI systems.

Supports corporate strategy and transformation initiatives through qualitative and quantitative analysis, problem-solving, recommendations, and cross-functional project management. The role leads strategic and operational projects, coordinates collaborators, facilitates decisions, communicates with senior leadership, and represents Corporate on firmwide initiatives. Success requires strong analytical, communication, collaboration, and organizational skills, plus experience in management consulting or business strategy and operations.

Provides compliance support for a broker-dealer by coordinating compliance programs, conducting surveillance reviews and forensic testing, analyzing regulatory developments, researching exceptions, and identifying compliance risks. The role also improves and automates employee compliance processes, supports new business initiatives, collaborates with legal and business teams, and develops pragmatic solutions to regulatory and operational issues.

Leads complex business analyses for Engineering, building financial and operational models, datasets, metrics, dashboards, and executive decision materials. Identifies efficiency and cost-saving opportunities, designs resource-allocation frameworks, manages recurring planning and reporting, and coordinates cross-functional initiatives across Engineering, Product, Modeling, Finance, and Corporate teams.