Top Tech Jobs & Startup Jobs in NYC, NY

Seeking an experienced Hardware Engineer to design, develop, and optimize server hardware and liquid cooling infrastructure, collaborating with cross-functional teams and vendors.

As a Firmware Engineer, you will develop and maintain firmware for embedded systems, test and validate firmware, collaborate with cross-functional teams, and document technical details.

As a Solutions Architect, you will be the primary technical contact for customers, helping establish and optimize their cloud infrastructure, engage with engineering teams, and provide insights on product development.

Manage strategic customer relationships, define technical requirements, oversee program execution, and facilitate collaboration across teams to ensure customer success in adopting CoreWeave's cloud services.

Lead the architecture and operations of network services, optimizing performance and scalability for AI workloads while ensuring security and compliance.

The role involves designing and implementing distributed storage solutions for AI workloads, developing scalable storage systems, optimizing performance, and mentoring engineers. It requires collaboration with various teams to ensure system reliability and efficiency.

Lead the evolution of CoreWeave AI Object Storage's security, manage cross-functional teams, and develop secure cloud-scale storage systems.

Design, implement, and automate scalable cloud security solutions and baselines across AWS/Azure/GCP. Build guardrails, IAM, detection/monitoring, configuration management, and data protection using IaC (Terraform) and everything-as-code. Collaborate with Product Engineering and security teams, produce technical documentation, and operationalize security tooling.

Lead and expand the SRE/Production Engineering team to ensure platform reliability, performance, and operational efficiency. Drive SRE strategy, automation-first practices (IaC, Terraform, Kubernetes), incident management, postmortems, SLO/SLA frameworks, on-call strategy, and system hardening. Collaborate with engineering, product, hardware, and security teams to build scalable, resilient, self-healing AI-focused cloud infrastructure.

Lead cross-functional programs to validate and optimize AI/ML infrastructure performance. Drive benchmarking, observability, hardware bring-up, release readiness, and measurable metrics across GPU-based clusters. Coordinate engineering, infrastructure, product, capacity, and go-to-market teams to operationalize benchmarking frameworks, prioritize performance work, and ensure platforms meet stability and performance standards for training and inference workloads.