01Overview
We are looking for a dynamic, highly motivated Services Manager to drive Engineering AI & Machine Learning (EnggAI) within Siemens Digital Industries Consulting. You will lead the adoption and delivery of nextgeneration, highfidelity simulation capabilities across the Siemens stack, bridging traditional CAE/Test with AI to advance digital twins in automotive, aerospace and manufacturing. You will solve complex mechanics problems, develop physicsinformed AI solutions, and lead a highperforming team to demonstrate, secure, and deliver cuttingedge client projects.
Key responsibilities :
Lead the consulting team to define, prototype, and deliver advanced AIdriven simulation projects that meet client strategic objectives and technical acceptance criteria.
Design and build highfidelity, physicsinformed AI models, prototypes and proofsofconcept that address realworld industrial engineering challenges.
Define technical architectures that integrate traditional CAE/Test methods (MBD, FEA/FEM, contact/friction, flexible bodies) with Engineering AI workflows to raise digital twin fidelity and runtime performance.
Oversee analysis of large CAE and physical test datasets to extract complex patterns and enable advanced diagnostics, prognostics, and anomaly detection.
Collaborate across product and engineering teams (PhysicsAI, RapidMiner, Simcenter3D, etc.) to industrialize methodologies into scalable, productionized processes and toolchains.
Provide technical leadership and mentorship: advise executive stakeholders, establish best practices in software libraries, data engineering, model validation, and agile delivery, and grow engineering talent.
Engage with clients to translate business needs into technical roadmaps, proposals, and measurable value demonstrations.
Required qualifications:
Advanced degree in Mechanical Engineering, Aerospace, Applied Physics, Computer Science, or related field, or equivalent experience.
Significant experience applying AI/ML to engineering simulation problems and delivering consulting or production projects for industrial clients.
Deep understanding of CAE/Test workflows (MBD, FEA/FEM), mechanics of contact/friction and flexible bodies, and how to combine them with datadriven models.
Strong architecture and system design skills for largescale simulation solutions, including GPU acceleration and numerical robustness tradeoffs.
Proven record of building prototypes and transitioning them into production workflows.
Excellent Client Communication Skills And Experience Leading Multidisciplinary Teams.
Proficiency in relevant software and tooling (Python, ML frameworks, data engineering tools, CAE toolchains, version control, CI/CD).
Preferred / differentiators:
Direct experience integrating test and simulation workflows and 1D system models.
Demonstrated ability to design simulation architectures balancing numerical fidelity and GPU scalability.
Exposure to agentic AI workflows, reinforcement learning for control/optimization, or other emerging industrial automation trends.
Prior experience delivering solutions within Siemens product ecosystems is a plus.
What we offer:
Opportunity to shape nextgeneration engineering AI for highimpact industrial applications.
Collaborative, multidisciplinary environment with access to leading simulation and AI technologies.
Leadership role with direct influence on product direction, client engagements, and team growth.
If you are passionate about advancing simulation fidelity through AI and enjoy leading technical teams to deliver measurable industrial value, apply to join our team. .
