Systems Engineer – AI Data Centers at GE Vernova

Job description

Job Description Summary Who We Are Power Conversion and Storage provides reliable, affordable and dispatchable integration of renewable, thermal and energy storage power technologies. The business unit, part of GE Vernova, works with utilities and developers to create solutions, that combine energy sources, efficient energy storage and software to create a more predictable supply of renewable electrons. Why We Come To Work Our team is dedicated to making a difference and creating a more sustainable future for all. We foster a dynamic and inclusive work environment where everyone is valued and can thrive. Whether you’re a seasoned professional or just starting your career in the clean energy industry, we invite you to join our team and be a part of a company that is making a real difference in the world. Overview Activities associated with the design of hybrid thermal, renewable and energy storage assetts for powering AI data centers and other mission-critical systems. The position will involve system-level engineering work across electrical, controls, thermal, software, and integration functions to define, assess, and advance complex storage based power solutions. The role will be focused on emerging AI datacenter applications where power quality, dynamic response, backup functionality, and hybrid system integration are critical. This includes helping define technical requirements, assess system performance, guide validation activities, and support strategic external engagement. Job Description Roles and Responsibilities Technical leadership and system definition: Participate/lead system-level engineering efforts for AI datacenter-focused Energy Storage applications, including requirements definition, architecture development, interface management, and performance assessment. Provide technical leadership across cross-functional teams to align work at the system level and drive resolution of complex engineering issues. Define and frame technical problems in new application areas where product capability, validation needs, and system behavior are still being established. Translate emerging customer and market needs into engineering direction and technical priorities. Strategic technical engagement: Lead technical collaboration with key external partners on AI datacenter power architectures, BESS application requirements, and qualification pathways. Support development of joint technical content such as whitepapers, seminars, and customer-facing technical material. Represent the team in technical discussions with customers, industry groups, and strategic partners. Help drive qualification efforts that expand deployment opportunities for GE Vernova energy storage and power conversion technologies. Identify emerging AI datacenter application needs and current product capabilities and gaps Battery degradation, validation, and technical risk reduction: Lead efforts to understand battery degradation under AI datacenter load profiles and other non-traditional duty cycles. Define test approaches and modelling needs to improve confidence in cell, module, and system-level lifetime predictions. Coordinate with research and engineering teams to close gaps in technical understanding and improve application readiness. Translate findings into design guidance, validation priorities, and system recommendations. Build out a broader degradation task-force team and coordinate work. Modelling, simulation, and application assessment: Development system-level models to assess battery and other storage performance in AI datacenter power applications. Evaluate system behavior for fast AI load transients, load shed and load acceptance, N 1 backup, frequency control in grid-forming mode, voltage and frequency ride-through, and interactions with turbine-based generation and other power assets. Use modelling and analysis to support architecture decisions, controls strategies, and technical risk reduction. Required Qualifications Bachelor s degree in Electrical, Chemical, Systems or Materials Engineering from an accredited university or college. Desired Characteristics Strong oral and written communication skills Ability to document, plan, market, and execute programs Self starter with willingness to learn across engineering disciplines Ability to work independently and a team environment Limited travel require Additional Information Relocation Assistance Provided: No #LI-Remote - This is a remote position

Requirements

Must-haves

Job Description Summary Who We Are
Why We Come To Work
Job Description Roles and Responsibilities
Participate/lead system-level engineering efforts for AI datacenter-focused Energy Storage applications, including requirements definition, architecture development, interface management, and performance assessment.
Provide technical leadership across cross-functional teams to align work at the system level and drive resolution of complex engineering issues.
Define and frame technical problems in new application areas where product capability, validation needs, and system behavior are still being established.
Translate emerging customer and market needs into engineering direction and technical priorities.
Lead technical collaboration with key external partners on AI datacenter power architectures, BESS application requirements, and qualification pathways.
Support development of joint technical content such as whitepapers, seminars, and customer-facing technical material.
Represent the team in technical discussions with customers, industry groups, and strategic partners.
Help drive qualification efforts that expand deployment opportunities for GE Vernova energy storage and power conversion technologies.
Identify emerging AI datacenter application needs and current product capabilities and gaps
Battery degradation, validation, and technical risk reduction:
Lead efforts to understand battery degradation under AI datacenter load profiles and other non-traditional duty cycles.
Define test approaches and modelling needs to improve confidence in cell, module, and system-level lifetime predictions.
Coordinate with research and engineering teams to close gaps in technical understanding and improve application readiness.
Translate findings into design guidance, validation priorities, and system recommendations.
Build out a broader degradation task-force team and coordinate work.
Modelling, simulation, and application assessment:
Development system-level models to assess battery and other storage performance in AI datacenter power applications.
Use modelling and analysis to support architecture decisions, controls strategies, and technical risk reduction.
Bachelor s degree in Electrical, Chemical, Systems or Materials Engineering from an accredited university or college.
Desired Characteristics
Strong oral and written communication skills

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

Platform: workday
Effort: long