Supply Chain Systems Development Manager

ST Logistics; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

ST Logistics is seeking a senior AI/ML leader to own the design and delivery of an AI-driven supply chain platform. You will oversee forecasting, procurement automation, and optimization engines, while mentoring engineers and shaping architectural best practices.

The role requires collaboration with business stakeholders and a strong focus on MLOps and scalable cloud deployment. You will drive design-thinking initiatives, ensure robust data platforms, and manage end-to-end delivery across

Qualifications

• 5+ years of software engineering experience, with 3+ years in AI/ML.
• Proven leadership of technical teams through multi-phase projects.
• Expert-level Python for ML modeling and backend systems; strong data platforms knowledge.

Responsibilities

• Lead development and integration of AI-driven supply chain platform covering forecasting, procurement, and logistics optimization.
• Mentor engineers and champion code quality, architecture, and MLOps.
• Translate business pain points into scalable technical requirements for ERP/WMS integrations.

Skills

Python for ML/backend

Time-series forecasting

Optimization (OR-Tools, Gurobi)

Databases / data lakes / Databricks

Cloud (AWS/GCP/Azure)

Containerization

MLOps / CI/CD

ERP/WMS integration

Communication / Stakeholder mgmt

Leadership / mentoring

Education

Degree in Computer Science or related discipline / OR related fields

Tools

SAP

Oracle

WMS

Job description

• End-to-End System Ownership - Lead the development and integration of a comprehensive AI-driven supply chain operating platform covering:
• Inventory Forecasting Demand: Deploy sophisticated predictive models to analyze inventory-specific demand patterns, incorporating seasonality, market trends, and lead-time variability to ensure optimal stock levels and availability.
• Procurement Management: Build automated, intelligent procurement systems that optimize vendor selection, purchase order generation, and cost-efficiency.
• Logistics Operations: Develop optimization engines for route planning, warehouse resource allocation, and real-time distribution efficiency.
• Strategic Leadership: Mentor a team of engineers, championing best practices in code quality, system architecture, and MLOps.
• Workflow Transformation: Utilize Design Thinking to audit, redesign, and automate legacy workflows. Ensure that process re-engineering and AI implementation work in tandem to eliminate bottlenecks.
• Customer& Stakeholder Partnering: Act as a technical authority in client-facing engagements. Translate complex business pain points into scalable technical requirements that deliver immediate business value.
• Cultural Leadership: Embody our corporate culture in all interactions, fostering a collaborative, transparent, and high-performance team environment.

Requirement

• Degree in Computer Science or related discipline, Operations Research, Industrial Engineering or Data Science.
• Experience: At least 5 years of software engineering experience, with 3+ years specifically in AI/ML development. Proven track record of leading technical teams through complex, multi-phase project lifecycles.
• Technical Proficiency: Expert-level Python for both ML modeling and backend systems. Proficient in time-series forecasting (Prophet, LSTMs, Transformers) and constraint-based optimization (OR-Tools, Gurobi). Have sound technical knowledge and skills related to databases/data lakes/data platforms (e.g.Databricks) setup and implementation.
• Domain Expertise: Comprehensive understanding of the integrated supply chain, specifically regarding the nuances of inventory forecasting demand, purchasing, warehousing and last-mile/distribution logistics. Proven record of delivering quantifiable ROI (e.g., reduction in inventory holding costs, improvements in delivery speed, or automated procurement throughput).
• Consulting Mindset: Ability to conduct process discovery, facilitate design-thinking workshops, and articulate technical roadmaps to non-technical executive stakeholders.
• Engineering Rigor: Deep knowledge of cloud infrastructure (AWS/GCP/Azure),containerization, and MLOps pipelines (CI/CD for data and model versions).Direct experience integrating AI solutions with major ERP (SAP, Oracle) or WMS platforms.
• Communication: Exceptional stakeholder management skills; capable of navigating complex conversations with both technical developers and business clients.