Top Tech Jobs & Startup Jobs in NYC, NY

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.

Sell Lightning AI’s technical, developer-focused AI platform to technical audiences. Responsibilities include outbound prospecting, lead qualification, product demonstrations, contract negotiation, closing deals, pipeline management, customer discovery, revenue target attainment, CRM data integrity, and collaboration with product, engineering, and marketing teams to improve sales processes and inform the product roadmap.

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.

Own cross-functional operations projects that remove growth blockers, diagnose organizational friction, and build scalable AI-powered internal tools and automations. Partner with teams across the company, drive project adoption, maintain internal operations documentation, support business programs, and measure outcomes using data. The role requires strong analytical thinking, stakeholder management, end-to-end project ownership, and hands-on experience building workflows with APIs, SaaS platforms, automation tools, and AI coding tools.

Lead and develop the customer success organization for technical, enterprise, and growth customers. Own adoption, retention, renewal readiness, customer health, expansion influence, and executive relationships. Build scalable onboarding, success planning, health scoring, forecasting, escalation, and expansion processes. Partner with Sales, Product, Engineering, Support, Marketing, and Revenue Operations to improve customer outcomes and product adoption while coaching teams and creating repeatable customer success playbooks.

Leads complex, cross-functional infrastructure programs spanning compute, networking, storage, observability, hardware, and datacenter operations. Owns program planning, milestones, dependencies, risks, and execution across multiple workstreams. Partners with engineering, operations, security, platform, and leadership teams to deliver network expansions, datacenter growth, hardware rollouts, GPU platform deployments, and infrastructure readiness. Provides leadership updates and improves execution frameworks, tooling, and program visibility.

Develop and post-train deep learning models while building systems, tooling, and workflows for training, evaluation, debugging, and deployment. Contribute to open-source projects, distributed AI infrastructure, backend services, and developer platforms. Collaborate with research, product, infrastructure, and customer teams to solve complex technical problems, prototype ideas, and productionize successful experiments.

Own the vision, roadmap, launch, adoption, pricing, and go-to-market for Lightning AI’s experimentation and post-training products. Define workflows for experiments, fine-tuning, reinforcement learning, evaluation, model comparison, and production handoffs. Collaborate closely with engineering, customers, executives, sales, Growth, and Finance. Drive product strategy, technical requirements, model evaluations, pricing, metrics, developer experience, and end-to-end execution for ML infrastructure and developer tooling.

Design and scale backend systems for AI agent orchestration, distributed workflows, experiment management, platform APIs, and developer tooling. Build reliable cloud-native infrastructure, improve observability and performance, partner across engineering and research teams, maintain software quality through testing and continuous delivery, and mentor engineers on distributed systems and backend best practices.