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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 career growth, ESOPs, Gratuity, PF and Health Insurance.