Technical Product Manager

SES AI Corp. (NYSE: SES) is dedicated to accelerating the world’s energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-enhanced, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials discovered by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and air), energy storage, robotics, and drones . To learn more about us, please visit: www.ses.ai What We Offer: A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock options program within our NYSE-listed company. The opportunity to contribute directly to a meaningful scientific project—accelerating the global energy transition—with a clear and broad public impact. Work in a dynamic, collaborative, and innovative environment at the intersection of AI and material science, driving the next generation of battery technology. Significant opportunities for professional growth and career development as you work alongside leading experts in AI, R&D, and engineering. Access to state-of-the-art facilities and proprietary technologies are used to discover and deploy AI-enhanced battery solutions. What we Need: The SES AI Prometheus team is seeking an exceptional Technical Product Manager to serve as the product leader who translates complex scientific and AI research into actionable roadmap deliverables. This role requires deep literacy in computational materials science and AI4Science to coordinate strategy across our research, engineering, and materials teams. As the Technical Product Manager, you will be the driving force behind the product lifecycle for our AI-driven materials discovery platform. Essential Duties and Responsibilities: Product Strategy & Roadmap Management Define the product vision and manage the roadmap for our AI for materials software, ensuring alignment across the entire organization. Translate complex scientific research and user needs into clear, customer-driven requirements for the engineering and research teams. Oversee AI for materials software and research coordination, managing cross-functional deliverables and maintaining feature velocity. Scientific & Research Alignment Bridge scientific research and engineering by defining how scientific findings (e.g., from DFT/MD simulations) are integrated into a scalable and usable platform. Identify opportunities for leveraging ML force-field models and AI molecular modeling to accelerate battery electrolyte design and performance. Ensure platform usability and scaling by defining requirements that serve both the deep research community and material production teams. Cross-Functional Leadership Drive cross-functional alignment and execution across research (Computational Chemistry), core Engineering, and experimental Materials teams within a fast-paced AI and battery/materials organization. Education and/or Experience: Education: Ph.D. in Computational Chemistry, Computational Materials Science, or a related quantitative field. Emphasis on Computational electrolyte design or interfacial chemistry is highly desirable. Domain Literacy: Deep technical literacy in Computational Chemistry, including proficiency in DFT and MD simulations for materials analysis. Product Management Experience: Proven experience as a Science-literate Product Manager overseeing the full software product lifecycle, specifically in the AI4Science or Materials Informatics space. Cross-Functional Management: Demonstrated experience defining and managing complex roadmaps and coordinating across research, engineering, and materials organizations. AI/ML Familiarity: Experience working with ML force-field models and other AI molecular modeling techniques. Preferred Qualifications: Industry Experience: Previous experience in relevant high-tech organizations such as Cusp.ai, XtalPi, scientific computing startups, or established AI4Science product teams. Broader Domain Application: Familiarity with computational tools and modeling related to other material science domains, such as aerospace thermal-barrier coatings or thermodynamics modeling in solar-cell materials. Scaling Scientific Tools: A track record of successfully bridging scientific research outputs with platform usability and scaling in a production environment.

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