HSBC

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We are currently seeking an experienced professional to join our team in the role of Tech Lead – Infrastructure Modernization &amp; AI Engineering
Business： CTO Infrastructure, Asia &amp; Middle East
Job ID：56478
We are seeking a visionary, hands-on Tech Lead to spearhead the next-generation modernisation of our high-scale Hong Kong platforms and regional architecture. As part of HSBC’s core technology and digital transformation blueprint for the next four years, this role will drive the transition from legacy stacks to resilient in-house managed, build using open-source architectures, hybrid-cloud deployments, and secure, production-grade AI engineering capabilities.
You will own the infrastructure technical roadmap, engineering execution, and architectural integrity for mission-critical client and operational platforms, ensuring low-latency performance, strict regulatory alignment, and continuous delivery at scale.
Key Responsibilities
<ul>
<li>Database &amp; Platform Modernization:</li>
<li><ul>
<li>Lead the modernization, advocacy and replatforming of database technologies from traditional relational DBMS (eg: DB2) to distributed databases (eg: Oceanbase) for our high-scale Hong Kong core services.</li>
<li>Lead the end-to-end Infrastructure refactoring and migration of core legacy services to modern, open-source-aligned, modern architectures.</li>
<li>Implement scalable containerization strategies (utilising advanced cluster networking and storage setups, e.g., Multus CNI integration) to handle heavy enterprise workloads.</li>
<li>Optimise high-throughput backend infrastructure, ensuring high availability, fault tolerance, and minimal technical debt across microservices.</li>
</ul>
</li>
<li>AI &amp; Data Engineering Integration:</li>
<li><ul>
<li>Architect and scale the foundational infrastructure required to support high-density AI and data engineering workloads, including enterprise-grade GPU clusters, high-performance distributed storage, and low-latency networking fabrics.</li>
<li>Establish enterprise-wide AI-Ops and MLOps platforms that automate model deployment, scaling, monitoring, and lifecycle governance across hybrid-cloud environments.</li>
<li>Optimize large-scale data ingestion and storage pipelines to support petabyte-scale real-time data streaming and distributed database architectures without compromising core banking availability.</li>
</ul>
</li>
<li>Engineering Excellence &amp; Leadership:</li>
<li><ul>
<li>Drive Agile delivery methodologies, replacing rigid release cycles with high-velocity minimum viable product (MVP) rollouts, rapid experimentation, and CI/CD automation.</li>
<li>Mentor and guide cross-functional software engineering teams, fostering a "fail-fast, learn-forward" engineering culture coupled with uncompromising production stability.</li>
<li>Collaborate closely with product owners, cybersecurity, risk, and regional stakeholders to align technical deliverables with strategic business outcomes.</li>
</ul>
</li>
<li>Infrastructure Resilience &amp; Cost Optimization:</li>
<li><ul>
<li>Implement automated capacity planning, autoscaling, and intelligent resource allocation models to optimize infrastructure expenditure for heavy machine learning and analytics workloads.</li>
<li>Ensure high availability, disaster recovery readiness, and rigorous fault tolerance across all core AI serving endpoints and distributed data nodes.</li>
<li>Maintain strict infrastructure compliance, security hardening, and zero-trust network segmentation for all AI processing pipelines and training environments.</li>
</ul>
</li>
</ul>
Requirements &amp; Qualifications
<ul>
<li>Experience:</li>
<li><ul>
<li>8+ years of software engineering experience within enterprise environments, with at least 3+ years in a technical leadership or principal architecture role.</li>
<li>Deep domain expertise in banking, fintech, or large-scale digital platform modernization.</li>
</ul>
</li>
<li>Technical Stack:</li>
<li><ul>
<li>Core Engineering: Advanced proficiency in modern backend languages (e.g., Java, Python, Go) and event-driven architecture (Kafka, RabbitMQ).</li>
<li>Cloud &amp; Infrastructure: Extensive hands-on experience with Kubernetes, OpenShift, cloud-native infrastructure, and complex network/storage plugins (such as Multus).</li>
<li>Data &amp; AI: Demonstrated experience integrating LLMs/GenAI pipelines via APIs, vector databases, and enterprise data mesh/mastering frameworks under strict security protocols.</li>
</ul>
</li>
<li>Methodologies:</li>
<li><ul>
<li>Proven track record of executing large-scale code migration projects, reducing legacy footprints, and enforcing strict automated testing, CI/CD pipelines, and infrastructure-as-code (IaC).</li>
</ul>
</li>
<li>Mindset:</li>
<li><ul>
<li>Exceptional stakeholder management skills, capable of bridging deep technical concepts with executive business strategy in a fast-paced regional hub like Hong Kong.</li>
</ul>
</li>
</ul>

Tech Lead - Core Systems Infrastructure Modernization & AI Engineering

Tech Lead - Core Systems Infrastructure Modernization & AI Engineering

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