About the Role We are seeking a Software Architect to lead the design and development of a next-generation dynamical simulation engine that combines high-performance numerical computation control-theoretic modeling and AI-driven predictive analytics You will architect and implement the computational core designing scalable precision-focused systems running on CPU and GPU and integrate AI ML modules for learning estimation and prediction This is a hands-on technically deep role with architectural ownership and cross-team leadership Key Responsibilities Core Architecture Simulation Engine Architect and implement a dynamical system simulation framework for complex time-dependent physical and engineered processes Develop and optimize numerical algorithms for multi-core CPUs and GPUs using C C Python and CUDA OpenCL Integrate control-theoretic models including feedback systems stability analysis and perturbation analysis Define simulation data structures solver architectures and modular interfaces for extensibility AI Predictive Modeling Integration Collaborate with AI ML teams to embed predictive models and data-driven controllers into the simulation loop Architect efficient data exchange and compute workflows between numerical solvers and AI inference engines Optimize hybrid AI physics simulation performance Performance Optimization Profile and tune performance-critical components for compute efficiency memory management and scalability Develop benchmarking tools and regression frameworks for algorithm validation Leadership Collaboration Lead a small team of simulation and algorithm engineers Work closely with the Application Tech Lead and UI backend teams for seamless integration Establish architectural standards review processes and documentation practices Requirements Bachelor s or Master s degree in Computer Science Electrical Mechanical Engineering Control Systems Applied Mathematics or a related field 10 years of experience in high-performance computational software development Deep understanding of Control theory dynamical systems and feedback mechanisms Numerical methods ODE PDE solvers and stability analysis Parallel and GPU computing CUDA OpenCL OpenMP C C Python and scientific computing libraries Proven experience integrating AI ML frameworks PyTorch TensorFlow with numerical systems Preferred Skills Experience building simulation engines from scratch not just using existing platforms Familiarity with distributed compute systems profiling and optimization tools Exposure to DevOps for scientific codebases CMake CI CD Docker Soft Skills Strong analytical and problem-solving skills rooted in mathematical reasoning Excellent communication and technical documentation abilities Proven leadership and mentoring capability Benefits We offer great growth opportunities ESOPs Gratuity PF and Health Insurance