Top Tech Jobs & Startup Jobs in NYC, NY

Build and operate production software, APIs, tooling, and automation for large-scale GPU, bare-metal, and HPC infrastructure. Responsibilities include provisioning, configuration, monitoring, lifecycle management, observability, hardware integration, reliability improvements, and infrastructure capacity deployment. The role partners with networking, data center, platform, and infrastructure teams to design scalable systems and define technical direction.

Drive data-informed decisions across Product, Sales, and Engineering by analyzing usage patterns, business performance, and trends. Build data pipelines, write SQL and Python analyses, create Looker and Data Studio dashboards, monitor opportunities and risks, and enable teams to use analytics tools effectively.

This is a general talent community opportunity rather than a specific open position. Lightning AI invites candidates to submit their information for consideration as future roles become available across U.S. and London hubs, with occasional remote opportunities. The company develops tools and infrastructure for building, training, and deploying AI systems and values ownership, urgency, communication, teamwork, continuous improvement, and long-term thinking.

Own strategic channel and technology partner relationships, develop joint business plans, create co-selling motions, identify partner-sourced opportunities, and drive pipeline, revenue, customer adoption, and field engagement. The role coordinates with sales, solutions engineering, marketing, customer success, and partner teams; manages enablement, executive alignment, quarterly reviews, partner workflows, and performance metrics while helping build an early-stage partner ecosystem.

Operate, scale, and optimize distributed storage infrastructure supporting large-scale AI/ML and HPC workloads. Build Python automation, manage Linux bare-metal systems, troubleshoot storage, hardware, networking, and operating system issues, and improve performance, reliability, monitoring, capacity planning, and lifecycle management. Collaborate with infrastructure, networking, platform, and data center teams on storage deployments and scaling strategies.

Build, validate, and operate large-scale bare-metal GPU infrastructure for AI/ML and HPC workloads. Responsibilities include managing Linux systems, image pipelines, test clusters, provisioning, firmware and driver validation, GPU diagnostics, performance analysis with NVIDIA DCGM, automation, virtualization, and hardware management interfaces. The role requires troubleshooting across hardware and software layers while collaborating with infrastructure, hardware, data center, platform, and ML teams.

The Senior People Partner will support engineering and technical leaders on organizational design, leveling, promotions, compensation, employee relations, performance management, and exits. The role will strengthen manager capabilities, improve technical hiring practices, build scalable people systems, and manage global employment complexity. This position requires strong judgment, communication, and influence in a fast-scaling, distributed AI and technology company.

Lead technical discovery, demonstrations, proof-of-concepts, and post-sales engagements for Lightning AI’s machine learning platform. Translate customer requirements into scalable AI solutions, support enterprise evaluations, partner with sales and cross-functional teams, influence product direction, and drive customer adoption. The role also involves coaching technical field leaders, supporting forecasting and deal execution, and contributing to solutions engineering growth in a fast-moving startup.

Operate and scale large GPU infrastructure platforms, including Linux systems, bare-metal environments, provisioning workflows, observability, and reliability automation. Responsibilities include platform deployment, incident response, break/fix operations, customer provisioning, on-call participation, infrastructure troubleshooting, and collaboration across engineering, networking, customer success, and software teams. The role also develops automation to reduce manual work and improve operational efficiency.

Own compensation philosophy, incentive and equity design, compensation planning cycles, market benchmarking, offer and leveling frameworks, and analytical models. Build compensation and equity tools, dashboards, and reporting for pay equity, offer competitiveness, retention risk, and performance cycles. Partner cross-functionally with People, Finance, and senior leaders to translate market and modeling insights into compensation decisions.