Logistics Automation Process Simulation Supervisor; AMR Focus

The Logistics Automation Process Simulation Supervisor leads the engineering team responsible for creating, testing, and optimizing digital twins of Autonomous Mobile Robot (AMR) fleets within automated fulfillment centers. This role focuses on virtually modeling fleet dynamics, navigation pathing, charging strategies, and traffic management to eliminate bottlenecks and validate throughput before physical AMR deployment.

• Lead AMR Simulation Projects
  :
  Oversee the creation of high-fidelity simulation models specifically focused on large-scale, multi-agent AMR fleets and grid-based storage systems.
• Optimize Fleet Dynamics
  :
  Evaluate and fine-tune AMR dispatching rules, pathfinding algorithms, layout configurations, and pick/drop station configurations using simulation data.
• Traffic & Congestion Management
  :
  Identify and mitigate virtual deadlock scenarios, aisle congestion, and battery charging infrastructure bottlenecks.
• Scalability & Stress Testing
  :
  Design and execute "what-if" testing matrices for fleet scaling, sudden seasonal order spikes, and individual robot failure modes.
• Cross-Functional Collaboration
  :
  Partner with AMR hardware vendors, software developers (WMS/WCS/Fleet Managers), and facility operations to align virtual models with real-world constraints.
• Team Leadership
  :
  Supervise a team of simulation engineers and data analysts, managing project timelines and assigning daily tasks.
• Executive Reporting
  :
  Translate complex simulation results into clear data visualizations to justify capital expenditure (Cap Ex) for robot procurement.

• Education
  :
  Bachelor’s degree in Industrial Engineering, Robotics Engineering, Supply Chain Engineering, or a related technical field.
• Experience
  : 4+ years of experience in logistics simulation engineering, with a heavy emphasis on mobile robotics, AGVs, or AMRs.
• Software Expertise
  :
  Advanced proficiency in simulation tools that support multi-agent and kinematics modeling (e.g., Any Logic, Siemens Tecnomatix Plant Simulation, Flex Sim, Visual Components).
• AMR Knowledge
  :
  Strong understanding of AMR fleet management systems, localization/mapping concepts, task allocation logic, and spatial coordination.
• Technical Skills
  :
  Proficient in Python, C++, or Java for custom behavior scripting within simulation models.

• Experience integrating simulation models with live vendor Fleet Management software via APIs.
• Familiarity with ROS (Robot Operating System) or VDA 5050 communication standards.

KUKA is an Equal Opportunity Employer committed to building an inclusive and diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status, protected veteran status, or any other factor protected by applicable federal, state or local laws.