Key Responsibilities

• Product Vision and Strategy: Define and execute the product roadmap for our Physics AI platform, which includes synthetic data generation using PINNS, model creation and fine tuning, model inference and API access to the entire suite of product capabilities
• Deep Technical Ownership: Drive roadmap development and work closely with the engineering and field teams to deliver the product, gather feedback and ensure that the customer is successful
• Customer-Centric Execution: Serve as the critical bridge between our Research team (who discover breakthroughs) and our Forward Deployed Engineering team (who embed with customers to integrate our tools). Translate high-level customer engineering problems into clear, prioritized requirements for ML and software engineering teams.  
• Enterprise Integration & Scalability: Ensure the platform is enterprise-ready, designing features for seamless interoperability with legacy CAE software and established data management systems (e.g., through connectors and API integration). Maintain a strong focus on enterprise-grade security and multi-cloud scalability.  
• Democratization of Simulation: For the Engineering Applications layer, focus on developing intuitive, no-code solutions tailored for engineers and technicians, abstracting the platform to enable rapid optimization and process control across the entire enterprise.  
• Market Leadership: Conduct continuous competitive analysis and customer research, specifically within high-impact sectors like Aerospace & Defense and Semiconductors, to maintain Luminary’s competitive advantage in AI-native simulation.  

Expertise and Qualifications

• Domain Expertise: Proven experience in one or more relevant technical domains, such as:
• • Simulation/CAE: Familiarity with Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), or other physics-based simulation tools. Experience with Geometry manipulation, meshing techniques a must.
  • Applied AI/ML: Experience shipping machine learning or data science models in a production environment, including familiarity with model training, data pipeline management, and validation techniques.
  • API First software: Proven experience building specs for API first software
• Excellent communication: Should have prior experience of working on highly technical problems with technical customer audiences
• Education: Bachelor’s or Master’s degree in a quantitative or technical field (Computer Science, Engineering, Physics, or Mathematics).
• Strategic Acumen: Demonstrated ability to define a multi-year product strategy and deliver incremental value in complex, regulated industrial environments.
• Collaboration: Exceptional ability to work with highly specialized teams, including Simulation Engineers, Machine Learning Engineers, and Data Scientists, turning deep research into practical, scalable product features.  
• Adaptability: The capability to quickly adapt to new technologies and methodologies as the tech landscape evolves.
• Teamwork and Communication: Strong interpersonal and communication skills, enabling effective collaboration with cross-functional teams, clear articulation of technical concepts, and mentorship of junior team members.
• Entrepreneurial Spirit: An entrepreneurial mindset that thrives in a dynamic, rapidly evolving environment (preferably at a startup) and is enthusiastic about driving innovation and growth and is self driven.