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A leading company in AI solutions seeks a Lead AI Engineer to develop scalable AI systems for supply chain challenges. This role requires deep expertise in software architecture and team leadership, along with technical proficiency in Python and cloud deployment practices. Join to make an impact in AI-driven business solutions and promote continuous improvement in a collaborative environment.
We are looking for a Lead AI Engineer with deep experience in supply chain AI solutions and a strong understanding of end-to-end software architecture, packaging, and deployment. This role is crucial to building scalable AI solutions that not only solve core supply chain problems but can also be deployed securely in client’s cloud environments—while protecting our intellectual property.
Responsibilities:
● Architect, design and build end-to-end AI-driven systems that seamlessly integrate research models into robust, scalable business solutions—anchored by clear, domain-specific logic.
● Translate business and retail-specific requirements into scalable and reusable software components.
● Design and develop modular, portable, and production-ready code that can be deployed across cloud platforms (AWS, GCP, Azure) or on-premise
● Define and enforce software architecture patterns, coding standards, and DevOps/MLOps best practices across the engineering team.
● Review code, lead design sessions, and ensure team deliverables meet security, performance, and maintainability standards.
● Lead internal knowledge sharing and foster a culture of continuous improvement.
● Lead team members both in Singapore and abroad to develop the solutions to solve business problems of our clients.
Requirements:
● Bachelor’s or Master’s degree in Computer Science, AI, Operations Research, or a related field.
● 3+ years in AI/ML engineering, with at least 2 years in a leadership or architectural role.
● Proficient in Python and core technical stacks, including:
o Scientific computing: NumPy, pandas, SciPy
o Databases: SQL (MySQL, PostgreSQL) and NoSQL (e.g: MongoDB)
o Testing frameworks: PyTest or equivalent for unit/integration testing
● Experience deploying software in cloud and on-prem environments (using Docker, K8s, CI/CD pipelines).
● Familiarity with secure code packaging practices (e.g., compiled binaries, encrypted containers, license enforcement).
● Deep understanding of OOP, architecture, microservices, API design, clean code, and versioning.
● Previous experience with deployment of AI models to production is a plus.
● Previous experience with inventory optimization, demand forecasting, or supply chain AI solutions is a plus.