Join our specialized team as a Custom Software Engineer, focusing on crafting innovative solutions through intelligent simulation, Digital Twins, AI, and data-driven decision-making. You will be instrumental in developing sophisticated Agent-Based Simulation (ABS) models designed to represent complex systems. This includes modeling autonomous entities, human behavior, and operational processes across diverse industries such as manufacturing, supply chain, logistics, healthcare, and energy. Collaboration with cross-functional teams, including simulation engineers, solution architects, AI specialists, and business consultants, is key to delivering transformative solutions that boost operational efficiency, resilience, and overall business outcomes.

Develop advanced Agent-Based, Discrete Event, and hybrid simulation models to tackle intricate business and operational challenges. Translate client requirements and complex business processes into effective simulation solutions and experimental scenarios. Conduct thorough model verification, validation, calibration, and sensitivity analysis to ensure the highest level of accuracy. Analyze simulation outputs to extract and present actionable insights to business and project stakeholders. Collaborate closely with engineering, analytics, AI, and business teams to deliver integrated simulation and Digital Twin solutions. Adhere to Agile methodologies, established engineering standards, and quality assurance practices throughout the delivery lifecycle. Create and maintain reusable simulation assets, comprehensive technical documentation, and valuable knowledge management artifacts.

A minimum of 5 years of dedicated experience in Discrete Event Simulation is essential. This role requires a 15-year full-time education background. Demonstrated expertise in developing and maintaining Agent-Based Simulation (ABS), Discrete Event Simulation (DES), and hybrid simulation models utilizing platforms like AnyLogic, Mesa, GAMA, and NetLogo. Proficiency in designing intelligent agent behaviors, decision logic, interaction mechanisms, and simulation architectures for complex systems. Strong command of Python, Java, SQL, and Object-Oriented Programming principles for building scalable and reusable simulation solutions. Experience with model verification, validation, calibration, sensitivity analysis, and optimization to ensure simulation accuracy and reliability. Ability to integrate simulation models with enterprise applications, databases, IoT data streams, and Digital Twin ecosystems. Application of Operations Research, Machine Learning techniques, and data analytics methodologies to enhance simulation outcomes and business decision-making. Familiarity with AutoCAD, Azure/AWS cloud platforms, Git, CI/CD pipelines, and Power BI for deployment, visualization, integration, and reporting.