AI Infrastructure Engineer – Emerging Technologies

This is a fully remote position, open to applicants in Ohio, +2 more states.

📋 Description

• Assist the VP of Technology Engineering & Innovation in assessing new AI infrastructure technologies and strategies for future-ready data centers.

• Examine AI workload characteristics such as: Training versus inference workloads, GPU usage patterns, dynamic workload fluctuations, rack-level power variability, and networking and latency needs.

• Evaluate the effects of AI workload behaviors on infrastructure resilience, scalability, efficiency, and operational design.

• Create technical recommendations and infrastructure strategies to support upcoming AI deployments.

• Review current and prospective AI computing platforms including NVIDIA GPU architectures, ARM-based platforms, custom AI accelerators and ASICs, optical networking and switching technologies, as well as emerging hyperscaler-designed AI chips.

• Analyze the implications of evolving chip architectures on rack density, power usage, cooling requirements, electrical distribution, mechanical infrastructure, spatial planning, and future development standards.

• Model current and anticipated AI rack power density trends, including existing high-density deployments (50–120 kW), near-term AI deployments (150–300+ kW), and future ultra-dense AI cluster scenarios.

• Assess the long-term impacts of emerging chip architectures on energy efficiency and future data center design and development standards.

• Support both conceptual and detailed design efforts for AI-ready data center infrastructure.

• Aid in creating long-term infrastructure roadmaps for high-density AI deployments, liquid cooling adoption, modular infrastructure strategies, utility coordination, grid-parallel and microgrid solutions, as well as future AI campus development.

• Evaluate the implications of AI infrastructure evolution on new developments, retrofits of existing facilities, construction methodologies, scalability, and future campus master planning.

• Collaborate with engineering, development, and construction teams to create scalable AI-ready infrastructure standards and deployment models.

• Work closely with the Energy Strategy Team to assess utility constraints, interconnection requirements, grid limitations, dynamic load fluctuation impacts, power quality and resiliency considerations, and onsite generation and distributed energy solutions.

• Support the analysis of grid-parallel and islanded microgrid architectures, fuel cells, Battery Energy Storage Systems (BESS), bridge power solutions, natural gas generation, and renewable integration opportunities.

• Evaluate the implications of AI workloads on substation development, transmission planning, utility coordination, and energy efficiency and PUE optimization.

• Examine how future AI compute growth will affect utility planning and power infrastructure strategies.

• Analyze current and emerging thermal management solutions, including air cooling, direct-to-chip liquid cooling, immersion cooling, rear-door heat exchangers, and hybrid cooling architectures.

• Assess the implications of ultra-high-density AI deployments on mechanical system design, water usage, cooling scalability, heat rejection strategies, thermal resilience, and future cooling infrastructure standards.

• Evaluate cooling technologies and infrastructure requirements as AI rack densities continue to rise.

• Directly interface with technology vendors, OEMs, utilities, and strategic partners in power generation, UPS systems, electrical infrastructure, cooling technologies, liquid cooling platforms, AI compute infrastructure, and networking and optical interconnect technologies.

• Lead technical evaluations of next-generation technologies concerning reliability, scalability, energy efficiency, sustainability, AI workload performance, construction complexity, and operational resilience.

• Support proof-of-concept initiatives, pilot deployments, and technology benchmarking efforts.

• Formulate executive-level recommendations regarding the adoption of emerging AI infrastructure technologies and strategic engineering standards.

• Collaborate with design engineering, construction, operations, energy strategy, procurement, utilities, technology partners, and external engineering firms and consultants.

• Assist in strategic planning initiatives and executive-level technical presentations.

• Help develop future infrastructure standards and innovation roadmaps for AI-enabled data center platforms.

⛳️ Requirements

• Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, Computer Science, Data Center Engineering, or a related technical field.

• At least 5 years of experience in one or more of the following areas: data center infrastructure, AI/HPC infrastructure, power systems engineering, cooling technologies, or advanced infrastructure engineering.

• Strong knowledge of emerging AI compute technologies and their implications for infrastructure.

• Ability to analyze complex technical systems and convert findings into actionable engineering and infrastructure strategies.

• Candidates must be authorized to work for any employer in the U.S. We cannot sponsor or transfer sponsorship for an employment visa at this time, including CPT/OPT.

🏝️ Benefits

• Understanding and adherence to Cologix’s information security, cybersecurity, privacy, and environmental management policies, procedures, and standards.

• Ensuring compliance with the requirements of both the Information Security Management System (ISMS) and the Environmental Management System (EMS).

• Remaining vigilant and reporting any information security or environmental incidents, vulnerabilities, risks, or non-conformities to the appropriate teams.

• Actively participating in Cologix’s efforts to maintain and enhance information security and environmental performance.