Top Engineering Jobs in New York City, NY

Own and evolve a Kubernetes-native test framework that qualifies host images on real hardware. Build test harnesses, extend coverage into HPC, Slurm-on-Kubernetes and firmware/hardware, keep CI fast and reliable at fleet scale, and own results, reporting, and triage. Collaborate with kernel, firmware, imaging, and HPC teams and explore LLM-driven log triage and failure classification.

Leads a full-stack Fleet Engineering team building Go and React/TypeScript tools for hardware ticketing, technician repairs, and fleet inventory workflows. Owns hiring, team development, product delivery, release cadence, reliability, observability, incident response, architecture, and cross-team APIs. Partners with operations stakeholders to improve data center hardware lifecycle management and fleet efficiency.

Develop and maintain firmware for embedded systems, collaborate with teams, troubleshoot issues, optimize performance, and mentor junior engineers.

Design and implement scalable, fault-tolerant Kubernetes control-plane components. Develop Helm charts, custom controllers and CRDs, build deployment automation, monitoring, dashboards, and participate in on-call operations to ensure platform reliability and operability.

As a Solutions Architect, engage with customers to architect cloud solutions, optimize workloads, and provide technical leadership while collaborating with engineering teams.

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.

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.