Top Tech Jobs & Startup Jobs

The CIO will build and lead the enterprise technology function for a rapidly scaling AI company. Responsibilities include enterprise technology strategy, architecture, ERP and business systems, AI-enabled automation, IT operations, governance, controls, vendor management, budgeting, and cost optimization. The leader will recruit and develop the technology organization, oversee implementation partners, establish scalable systems and standards, and partner with executive leadership to align technology investments with business growth and public-company readiness.

The IT Systems Engineer will manage Windows Server environments, VMware, Citrix infrastructure, and Ivanti Endpoint Management, while providing technical support and implementing security practices in an enterprise environment.

The IT Consultant engages with clients to understand requirements, provides strategic guidance, implements tech solutions, and supports IT initiatives while fostering strong relationships.

Lead design of GPU servers and rack-scale infrastructure for AI workloads, partnering with GPU vendors, ODMs/OEMs, and data center teams. Own mechanical layout, power distribution, thermal design, cable management, validation, and production readiness while balancing performance, reliability, serviceability, and cost. Influence hardware standards and strategy across large-scale deployments.

Build and scale distributed training infrastructure for large AI models across GPU clusters. Improve training reliability, efficiency, fault tolerance, checkpointing, and resource utilization. Integrate training systems with production ML pipelines, develop tooling and automation to improve developer experience, diagnose training throughput and stability issues, and establish operational best practices for a growing AI infrastructure platform.

Design, build, and operate GPU-focused virtualization and Kubernetes orchestration systems for multi-tenant AI/HPC clusters. Implement automated provisioning, workload scheduling, resource management, and tooling to scale, secure, and run GPU compute reliably across production environments while partnering with hardware, networking, and platform teams.

Optimize GPU kernels and data-plane performance for large-scale AI workloads by profiling, identifying bottlenecks, tuning kernels, developing benchmarks and tooling, and collaborating with ML and platform teams to maximize GPU utilization, throughput, and reliability.

Build and operate production-grade model-serving and inference systems focused on high throughput, low latency, GPU efficiency, scalability, and reliability. Collaborate with GPU performance, training, orchestration, and infrastructure teams to optimize inference performance, design scalable systems, implement monitoring/alerting, and resolve production capacity and reliability issues.

Lead utility infrastructure projects focusing on water, wastewater, and stormwater initiatives while managing budgets, schedules, and client interactions.

The Senior Project Engineer designs and delivers water infrastructure projects, collaborates with project managers, prepares technical documents, and mentors junior staff.