Senior Data Center Systems Engineer -- AI Infrastructure & Performance Optimization
At a glance
Senior ML Platform & Ops role at Jci. New Freedom-Pennsylvania-United States of America · full-time · no salary stated · we estimate $180,000–$245,000 across the United States.
Jci has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Set up and run AI/HPC clusters for LLM and VLM work, simulations, and infrastructure stress tests
- Install and commission liquid cooling equipment, including cold plates, CDUs, immersion systems, and hybrid setups
- Test CPU and GPU workloads under different conditions to measure heat and power behavior
- Combine IT telemetry with mechanical and electrical data in digital twins, then analyze system readings to improve efficiency
- Work with thermal and controls teams to validate cooling, connect monitoring platforms, and share findings through reports and industry events
What you bring
- A master's or doctorate in electrical engineering, mechanical engineering, computer science, or another listed field
- Five to seven years working in AI/HPC infrastructure, data center operations, or a related technical role
- Hands-on experience running GPU-based AI workloads, including LLM or VLM tasks, training, inference, and HPC simulations
- Working knowledge of AI hardware, data center cooling and power systems, networking, and infrastructure monitoring or modeling
Who this fits
This senior role suits someone who can work independently with limited supervision and handle complex infrastructure projects. You’ll collaborate across thermal and controls teams, and represent the work at conferences, technical forums, and customer meetings.
From the employer
Senior Data Center Systems Engineer -- AI Infrastructure & Performance Optimization
Job Description
Position Summary
Johnson Controls' Data Center Thermal Solutions team is seeking a Senior Data Center Systems Engineer for the Advanced Technology & Innovation group. This role bridges AI/HPC computing systems with data center infrastructure, focusing on optimizing the interdependencies between computing workloads and cooling efficiency. The ideal candidate will be highly self-driven, able to work independently with limited supervision, and bring deep expertise in GPU-based AI workloads combined with comprehensive understanding of data center infrastructure systems.
Key Responsibilities
- Deploy, configure, and manage AI/HPC compute clusters running diverse workloads including LLM training and inference, VLM applications, HPC simulations, and stress testing scenarios.
- Deploy and commission liquid cooling hardware including direct-to-chip cold plates, CDUs, immersion systems, and hybrid cooling solutions for high-density AI infrastructure.
- Design and execute workload management strategies to evaluate thermal and power characteristics across CPU and GPU-based AI nodes under varied operational conditions.
- Develop system-level digital twin simulations integrating IT telemetry with mechanical and electrical infrastructure data to model cooling and computing efficiency interdependencies.
- Extract and analyze telemetry data from IT nodes, GPUs, CPUs, and thermal systems including chillers, cooling towers, pumps, and CDUs to optimize performance and energy efficiency.
- Collaborate with thermal engineers and controls teams to validate cooling system performance under real-world AI/HPC workloads and support NPI development initiatives.
- Integrate and leverage DCIM and BAS platforms for holistic infrastructure monitoring, predictive analytics, and operational optimization.
- Author technical reports and industry white papers documenting research findings, best practices, and performance benchmarks for AI data center infrastructure.
- Represent Johnson Controls at industry conferences, technical forums, and customer engagements to share innovations and establish thought leadership in AI infrastructure optimization.
- Interface with hyperscalers, OEMs, and technology partners to align infrastructure solutions with evolving AI hardware and workload requirements.
- Contribute to technical publications, patent filings, and industry standards related to data center systems optimization.
Qualifications
- PhD or Master's degree in Electrical Engineering, Mechanical Engineering, or Computer Science.
- 5-7 years of professional experience in AI/HPC infrastructure, data center operations, or related technical roles.
- Prior experience working in data center environments strongly preferred.
- Proven hands-on experience deploying and managing LLM, VLM, training, inference, and HPC simulation workloads on GPU-based AI infrastructure.
- Deep understanding of AI hardware architectures (NVIDIA H100/H200, AMD MI300, etc.) and their thermal/power characteristics across diverse workloads.
- Strong knowledge of data center mechanical systems (cooling distribution, heat rejection), electrical systems (power distribution, UPS), and networking architectures (InfiniBand, Ethernet fabrics).
- Proficiency with DCIM platforms, BAS integration, and digital twin modeling tools for infrastructure simulation and optimization.
- Experience with stress testing tools, workload orchestration platforms (Kubernetes, Slurm, etc.), and telemetry collection frameworks.
- Demonstrated ability to work independently, manage complex projects, and deliver results with minimal supervision.
- Track record of innovation and cross-functional collaboration in data center or AI infrastructure environments.
- Strong technical communication and presentation skills for conference participation and white paper authorship.
Johnson Controls International plc. is an equal employment opportunity and affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, protected veteran status, genetic information, sexual orientation, gender identity, status as a qualified individual with a disability or any other characteristic protected by law. To view more information about your equal opportunity and non-discrimination rights as a candidate, visit EEO is the Law. If you are an individual with a disability and you require an accommodation during the application process, please visit here.