Description
We are currently seeking an experienced professional to join our team in the role of Principal Engineer (Group AI Platforms).
The Group AI Platforms team sits within CTO Platforms, part of HSBC’s Chief Technology Office (CTO). We build shared AI foundations that enable teams across the Bank to deliver AI solutions faster, more safely and at scale.
As a Principal Engineer in Group AI Platforms, you’ll shape the technical strategy and provide architecture oversight for HSBC’s next-generation AI platform. You’ll help establish the engineering foundations that enable AI capabilities to be delivered reliably, securely and at scale across the Bank.
The role will focus on strengthening the resilience, scalability, performance and operability of core AI platform services, including the AI Gateway, security guardrails, model hosting and related foundation services.
You’ll help define the target architecture and engineering standards for a unified gateway ecosystem spanning LLM Gateway, MCP Gateway and Agent Gateway, alongside Guardrails as a Service.
You’ll also identify and adopt relevant advances in AI and cloud-native engineering to ensure the platform remains secure, efficient and fit for the evolving needs of the Bank.
As a senior technical authority, you’ll establish engineering best practice, drive adoption across platform delivery teams and raise the standard for production readiness.
You’ll champion AI-native development practices that improve delivery efficiency, software quality and engineering decision-making,while ensuring that human accountability, security, resilience and responsible use remain central.
What you will need to succeed in the role:
- Significant experience operating as a Principal Engineer or senior technical authority in a large-scale enterprise technology environment.
- Extensive experience designing, building or operating shared platforms used by multiple product and application teams.
- Strong experience with gateway platforms, service control planes, API mediation layers, service meshes or comparable enterprise integration platforms.
- Experience designing platforms that support high availability, high concurrency, low latency, traffic management, rate limiting, routing, authentication and policy enforcement.
- Practical understanding of security controls for AI systems, including: policy enforcement and access control; data protection and secure integration; auditability and traceability; model and capability governance; and runtime guardrails and monitoring.
- Strong knowledge of production readiness, including non-functional requirements for resilience, observability, security, performance, scalability, operability and recoverability.
- Working knowledge of Golang and/or Python for platform tooling, service integration, experimentation or adjacent production development.
- Experience with Kubernetes and cloud-native production systems, including deployment patterns, networking, scaling, service discovery, resilience and incident troubleshooting.
- Experience implementing modern delivery practices such as automated testing, continuous integration and delivery, canary deployment, progressive delivery, A/B testing and automated rollback.
- Familiarity with LLM gateways, MCP-based integrations, agent platforms or comparable emerging AI infrastructure is desirable.
- Strong communication and stakeholder-management skills, with the ability to explain complex technical trade-offs clearly to both technical and non-technical audiences.
- A collaborative leadership style and a commitment to knowledge sharing, coaching and raising engineering standards across a global team.