Software Engineering Manager (AI Supply Chain Solutions)

[Job ID: 1678283]

Responsibilities

• Spearhead the design, development, and integration of an end-to-end AI-powered supply chain platform.
• Develop predictive demand forecasting models to optimize inventory planning and stock availability.
• Build intelligent procurement solutions that enhance vendor selection, automate purchasing workflows, and improve cost efficiency.
• Create logistics optimization engines for route planning, warehouse resource allocation, and distribution performance.
• Lead and mentor software engineers and AI developers, promoting engineering excellence, code quality, and MLOps best practices.
• Drive workflow transformation initiatives through process redesign, automation, and AI implementation.
• Partner with business stakeholders and customers to translate operational challenges into scalable technical solutions.
• Define technical architecture, implementation roadmaps, and solution strategies aligned with business objectives.
• Integrate AI applications with enterprise systems and data platforms to ensure seamless operational performance.

Requirements

• Degree in Computer Science, Data Science, Operations Research, Industrial Engineering, or a related discipline.
• At least 5 years of software engineering experience, including 3 years of AI/ML development experience.
• Proven experience leading technical teams through complex, multi-phase projects.
• Strong proficiency in Python for machine learning development and backend application engineering.
• Hands-on experience with time-series forecasting models such as Prophet, LSTM, and Transformer architectures.
• Experience with optimization frameworks including OR-Tools, Gurobi, or similar technologies.
• Practical knowledge of database, data lake, and data platform implementation, including Databricks or similar solutions.
• Deep knowledge of cloud platforms such as AWS, Azure, or GCP.
• Experience with containerization technologies and MLOps practices, including CI/CD pipelines for data and model deployment.
• Hands-on experience integrating AI solutions with ERP platforms such as SAP or Oracle and Warehouse Management Systems (WMS) is an added advantage.

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