Top Tech Jobs & Startup Jobs in NYC, NY

The Site Selection Manager will lead procurement for data center sites, conduct due diligence, maintain relationships with stakeholders, and negotiate leases.

Lead detection engineering end-to-end: threat modeling, detection-as-code, deployment, tuning, and retirement. Build and maintain SIEM/EDR pipelines, run threat hunts, automate triage, and lead incident response with root-cause writeups tied to durable detections.

Build and lead detection engineering: create telemetry pipelines, detection-as-code with versioning and CI, write cloud and endpoint detections, automate triage/enrichment in Python, lead high-severity incident response, and partner with corp IT and infrastructure to obtain telemetry and remediate root causes.

Lead Fluidstack's editorial voice and content strategy for technical audiences. Turn complex infrastructure, AI, and energy work into credible long-form essays, launch messaging, and executive communications. Build and run an editorial pipeline, set writing standards, partner with founders and engineers, and ship timely, high-quality public-facing content.

Own roadmap and product direction for ontology and data products. Translate messy operational domains into data models and specs. Ship end-to-end with engineers, validate with stakeholders, and define metrics proving operational leverage.

Lead end-to-end R&D program plans for hardware and infrastructure: scope, sequencing, owners, and critical path from concept through prototype, qualification, and production handoff. Run NPI programs, coordinate design reviews, procurement, lab/test capacity, surface risks, drive cross-functional execution with manufacturing, supply chain, and deployment, and build leadership reporting while optimizing for velocity.

Own and scale the GPU compute fleet: build metrics, alerting, observability, and repair automation; design GPU qualification/burn-in pipelines; own Redfish/BMC tooling and firmware telemetry; run incidents, eliminate toil, and deliver end-to-end reliability and orchestration for Kubernetes and bare-metal compute at hyperscale.

Build and operate large-scale GPU compute fleet tooling: metrics pipelines, alerting, Redfish/BMC telemetry, repair/RMA automation, GPU qualification, and orchestration for Kubernetes and bare-metal deployments. Own reliability, scalability, incident response, and automation to minimize manual toil.

Model and track fleet capacity (power, space, cooling, compute), forecast constraints, connect deployment schedules to sellable capacity, run scenario analyses to inform allocation and deal decisions, and build executive-ready reporting.

Build AI-powered internal tools and shared AI infrastructure (agents and skills), integrate LLMs with internal systems, design and ship web applications, and enable cross-functional adoption through documentation and support.