Principal Technical Product Manager, Catalysis

Role overview A principal product manager opportunity to own a catalysis vertical within an AI-driven materials discovery platform. The role carries a dual mandate: translating government-funded R&D contract deliverables into shipped product capabilities, while building the commercial foundation to convert a funded research workstream into a durable, product-led business serving the broader materials and process-chemistry market. It blends deep scientific product thinking with enterprise go-to-market execution at the intersection of applied chemistry, simulation, and national-scale R&D programs.

Responsibilities - Own the end-to-end catalysis product strategy, vision, and roadmap, balancing contractual milestones, vertical scientific depth, and commercial expansion into adjacent markets. - Work closely with application scientists and business development to translate field insights, benchmark data, and customer feedback into prioritized product requirements and personas. - Convert program objectives into clear product requirements, a vertical roadmap, and the evidence packages required for formal contract fulfillment notices. - Define dataset and model requirements spanning chemical coverage, fidelity, and benchmarking, partnering with scientific and machine learning teams to direct simulation investment. - Drive the roadmap from property and energetics prediction toward reaction-level modeling so predictions can be validated against a customer's actual process rather than assessed in isolation. - Quantify customer value across yield, selectivity, catalyst life, energy efficiency, and emissions, and equip go-to-market and application science teams with that framing.

Requirements - Significant experience as a senior or principal product manager for technical or scientific software products, ideally with vertical ownership in a complex domain. - Understanding of machine-learned interatomic potentials, spin polarization in transition-metal systems, and how to evaluate ML models against experimental or first-principles reference data. - Track record building product-led growth motions for technical software, including self-serve adoption and land-and-expand commercial models. - Prior product or business development engagement with catalyst manufacturers, chemical producers, refiners, or semiconductor ecosystem partners such as fabs, equipment OEMs, and precursor suppliers. - Experience with multi-tenant SaaS, API governance, and enterprise security and compliance requirements. - An advanced degree in computational chemistry, chemical engineering, catalysis, materials science, or a related field.

Nice to have - Familiarity with the trade-offs between DFT, semi-empirical methods, and ML potentials, and a clear view on where each approach applies. - Experience structuring commercial offerings that combine simulation software with scientific services or partnership programs.

Benefits and work setup - Fully remote work with flexible paid time off, company-wide seasonal breaks, and support for flexible arrangements. - Competitive base salary, performance-based incentives, and equity participation. - Comprehensive medical, dental, and vision coverage with employer contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits. - Continuous learning opportunities through on-the-job development, cross-functional collaboration, and access to internal learning programs.