About Us

OptiMax AI Limited is a cutting-edge artificial intelligence company based in Hong Kong, dedicated to developing secure, controllable, and efficient enterprise-grade private supply chain large models. Our vision is to become the "AI Decision Brain" that powers intelligent enterprise operations. Founded in September 2025, OptiMax AI is backed by a stellar technical vision and a top-tier team, and is a key startup supported by the Hong Kong Innovation and Technology Commission's RAISe+ programme. We are AI-empowered and data-driven, committed to facilitating profound digital and intelligent transformation and decision-making upgrades for global enterprises.

Join us and help shape the future of enterprise intelligent decision-making!

About the Role

As a Data Platform Architect at OptiMax AI, you will be the "foundation" builder and chief engineer of all the company's intelligent products. The data platform you design and lead to build serves as the sole trusted data source and core backend for large model training, AI decision-making, and various upper-layer applications. Your responsibilities extend far beyond technology selection. You need to deeply understand the complex and diverse traditional management information systems on the client side, design robust data bridges and channels, and ensure data flows and integrates safely and efficiently between enterprises' existing systems and our AI platform like blood—ultimately activating the potential value of data.

Key Responsibilities

• Top-Level Architecture Design: Responsible for the overall architecture design, technology selection, and evolution planning of the company-level data platform, ensuring the platform's outstanding performance in security, scalability, stability, and cost efficiency.

• Data Integration & Governance: Lead the construction of an end-to-end data pipeline covering multi-source data collection, cleaning, transformation, and storage. Pay special attention to achieving intelligent data identification, classification, and maintenance through in-depth integration with large model systems.

• Enterprise System Integration: Act as a technical authority, leading the design of integration solutions with clients' existing data systems (including traditional management information systems such as ERP, MES, and SCM) and solving core technical challenges in heterogeneous system integration.

• Team Leadership & Implementation: Lead the data development team to transform architectural blueprints into high-quality engineering implementations, formulate development specifications, conduct code reviews, and ensure on-time project delivery.

• Cross-Departmental Technical Collaboration: Work closely with algorithm and product teams to deeply understand their data needs and challenges, providing powerful and reliable data infrastructure support for AI model training and inference.

We're Looking For

Essential Qualifications:

• Master's degree or above in Computer Science, Software Engineering, or related fields, with 3+ years of experience in data development and architecture.

• Proven track record of designing and leading the construction of medium-sized or larger data platforms/data middle platforms from 0 to 1.

• Proficiency in the big data ecosystem (such as Hadoop, Spark, Flink, Kafka, etc.) and modern data warehouse technologies (such as DataLakehouse).

• Rich experience in enterprise system integration, with a deep understanding of data models and interface characteristics of traditional management information systems (such as SAP, Oracle EBS, Kingdee, etc.).

• Excellent team leadership, communication, and project promotion abilities, capable of mapping technical blueprints and leading the team to implement them.

Preferred Qualifications:

• Experience leading a data development team of 5 or more members.

• In-depth understanding and practical experience in data governance, metadata management, and data security.

• Familiarity with the large model technology stack, with forward-looking thinking or practice in the application of LLMs in data governance, ETL, and other fields.

• Experience in data platform architecture in fields such as manufacturing and supply chain.