Technology Architect

15 years

0 Lacs

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Job Type

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Job Description

Project Role : Technology Architect
Project Role Description : Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs.
Must have skills : FEA Simulation
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary: We are seeking a Simulation Architect with a deep understanding of how simulation technologies can enable, accelerate, and augment AI systems. This role combines expertise across simulation domains - physics-based, discrete-event, agent-based, and system-level modeling with modern AI methods like ROMs, PINNs, surrogate modeling, and synthetic data generation. You will architect and implement simulation-driven AI pipelines that support predictive analytics, digital twins, and autonomous decision-making in complex engineering and manufacturing environments. Roles & Responsibilities: - Design and orchestrate simulation pipelines that augment AI, including: - Using simulation models in AI pipelines to enhance capabilities. - Generating synthetic training data from simulations. - Validating AI models in virtual testbeds. - Providing ground truth or constraint enforcement via simulation. - Build and deploy Reduced Order Models (ROMs) to approximate high-fidelity simulations for real-time or iterative use in AI workflows. - Develop and integrate Physics-Informed Neural Networks (PINNs) for learning physical behavior from sparse data while preserving physical laws. - Leverage physics-based simulation tools (FEM, CFD, Multiphysics) and combine it with data-driven AI approaches for hybrid modeling. - Enable co-simulation and AI-in-the-loop scenarios across domains (control, structural, thermal, fluid, logistics). - Collaborate with data science, simulation, controls, and software teams to embed AI-ready simulation outputs into system workflows. - Optimize compute performance for simulation+AI pipelines using cloud-native infrastructure (GPU clusters, containers, batch workflows). - Contribute to the design and validation of AI-augmented Digital Twins, including behavioral, physical, and predictive models. - Champion co-simulation architectures, surrogate modeling, and tool integration across commercial software (ANSYS, COMSOL, Abaqus) and scripting environments (Python, MATLAB, Modelica). - Provide technical leadership and mentorship, guiding engineering teams in scalable simulation, best practices and architectural patterns suited for fusion of Simulation and AI domains. - Actively lead and participate in sales pursuits and pre-sales engagements, with responsibility for new project wins. This will involve multiple discussions and presentation of our capability and solutions to potential clients and other Accenture stakeholders/ leader. - Active participation and leadership in driving industry related thought leadership activities like patents, authoring whitepapers/ POVs, proof of concepts, conference/ academia presentations, capability presentations etc. - Work with global clients and cross-functional teams in a multicultural and distributed environment. Professional & Technical Skills: Must have Skills: - Strong experience with one or more simulation paradigms: - Physics-based simulations (e.g., ANSYS, COMSOL, Simcenter) - Discrete-event simulation (e.g., Simio, JaamSim, AnyLogic) - Agent-based or system-level modeling (e.g., NetLogo, Simulink, Modelica) - Proficiency in developing Reduced Order Models (POD, DMD, Autoencoder-based) and deploying them for fast inference. - Experience implementing or applying PINNs using frameworks like NVIDIA Modulus, DeepXDE, or custom architecture. - Skilled in Python and common ML frameworks (PyTorch, TensorFlow, scikit-learn), with solid understanding of numerical methods and differential equations. - Strong foundation in applied physics, engineering mathematics, or control systems. - Experience of developing AI applications in digital twins, design optimization, or predictive maintenance. - Cloud engineering background, including automation, orchestration, and deployment of simulation pipelines in scalable environments. - Experience with manufacturing, industrial automation, automotive, or aerospace sectors. Good to Have Skills: - Familiarity with hybrid modeling (first principles + data-driven). - Background in digital twin development for factory planning, robotics simulation, or predictive maintenance - Familiarity with FMI/FMU, OpenModelica, OpenUSD, or robotics simulation standards. - Exposure to AI/ML-driven simulation workflows, Physics-informed ML, surrogate modeling, generative AI tools for model generation and behavior prediction. Additional Info: - This position is based at Bengaluru, Pune - Candidate should have a minimum 7 years of Industry Experience - Bachelor's or master's in engineering, Physics, Applied Mathematics, or related; PhD preferred.

15 years full time education

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