# Retail Platform Principal Engineer **Company**: HSBC **Location**: Guangzhou, Guangdong **Experience**: senior **Job type**: full-time **Category**: Engineering **Industry**: Finance **Apply**: https://portal.careers.hsbc.com/careers/job/563774608800937?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_2d283414-103 ## Description We are currently seeking an experienced professional to join our team in the role of Retail Platform Principal Engineer in WPS Technology. Responsibilities: - Provide strategic technical leadership across engineering projects, ensuring alignment with business goals, architecture principles, and regulatory/compliance requirements. - Architect and design scalable, resilient, secure microservices and event-driven systems to support high-throughput financial services workloads. - Lead adoption and governance of engineering standards, patterns, and best practices (API design, domain-driven design, CI/CD). - Hands-on development and code review in core platforms; set standards for software craftsmanship across Modern Tech stacks and cloud-native services. - Mentor and coach senior engineers and engineering leads; run regular technical deep dives, architecture reviews, and cross-team workshops. - Lead and facilitate blameless post-mortems and structured root cause analysis (RCA), driving remediation plans and lessons learned into the development lifecycle. - Own the Tech Risk Control 'book of work': maintain backlog of control remediation tasks, coordinate with Risk/Compliance to define mitigations, track progress, and ensure audit readiness. - Drive the integration of AI/ML capabilities into production systems with appropriate controls for governance, model risk, explainability, and data privacy. - Collaborate with product, security, ops, and data teams to prioritise technical debt, reliability improvements, and platform investments. - Represent engineering in stakeholder forums, technical governance boards, and external partner engagements. What you will be doing: - Act as the technical owner for core platform domains, driving architecture, design, and delivery across backend, data streaming, and cloud infrastructure; focus deeply on 2-3 areas (e.g., Java/Spring, Kafka/Stream Processing, Cloud/Kubernetes). - Lead targeted technical deep-dives (2-3 per quarter) to resolve architectural trade-offs, eliminate chronic pain points, and transfer knowledge across teams. - Own and deliver the Tech Risk Control book-of-work items for your area: define remediations, coordinate cross-functional delivery, produce evidence for audits, and close out controls. - Run structured root-cause analysis and blameless post-mortems for major incidents, translate findings into prioritised fixes, and ensure follow-through. - Provide hands-on technical direction: participate in design reviews, code reviews, prototyping, and proof-of-concepts to validate architecture decisions. - Mentor senior engineers and engineering leads; raise team capability through coaching, workshops, and documented standards/patterns. - Collaborate with product, security, data, and ops to align technical strategy with business objectives, regulatory requirements, and non-functional goals (scalability, resilience, security). - Drive adoption of cloud-native and DevOps practices (CI/CD, observability) and ensure production readiness for new services and AI/ML components. Qualifications Certifications & Education: - University degree in Computer Science, Engineering, or related discipline; MSc/PhD preferred. - Cloud certification(s) strongly preferred: AWS Certified Solutions Architect Professional or DevOps Engineer, Microsoft Certified: Azure Solutions Architect, or Google Professional Cloud Architect. - Desirable: Kubernetes (CKA/CKAD), security or data governance certificates. Preferred Qualifications: - Experience in financial services or regulated industries with demonstrable knowledge of regulatory controls, audit preparation, and model risk governance. - Contributions to open source projects or academic/industry research; speaker at technical conferences is a plus. - Proven ability to lead cross-functional engineering teams through technological transformations, and to operationalise AI safely at scale. Deliverables & Success Measures: - Architecture and platform designs that meet non-functional requirements (scalability, resiliency, security). - Successful delivery of prioritised Tech Risk Control book-of-work items and remediation actions. - Reduction in incident mean-time-to-detect and mean-time-to-recover through improved observability, RCA, and runbooks. - Mature AI/ML deployment pipelines with documented governance, monitoring, and model lifecycle controls. - High team engagement, evidence of knowledge transfer via deep dive sessions, and measurable uplift in engineering capability. Technical Skills & Experience: - Strong Java expertise (Java 8/11/17/21/25), demonstrated through large-scale, production systems. - Deep experience with Spring ecosystem: Spring Boot, Spring Cloud, Spring Security, Spring Data, and related tooling. - Microservices and cloud-native architectures: containerisation (Docker), orchestration (Kubernetes), service mesh (Istio/Linkerd), and 12-factor app principles. - Event streaming and messaging: Apache Kafka (Kafka Streams, ksqlDB), Confluent tooling, and best practices for exactly-once semantics and fault-tolerant processing. - Data platform familiarity: batch/stream processing (Spark, Flink), data lakehouse concepts (Delta Lake), and data governance tools (e.g., Apache Atlas, Apache Falcon, or equivalent). - AI/ML/LLM productionisation: hands-on with MLOps and Model frameworks (LangGraph, Agent Development Kit, Microsoft Agent Framework); experience deploying and operating LLMs (e.g., Falcon family or other LLMs), embeddings, RAG architectures, and frameworks (LangChain, LlamaIndex). - Observability, reliability, and performance engineering: Prometheus/Grafana, ELK/EFK, distributed tracing (Jaeger/Zipkin), profiling, and tuning high-throughput systems. - DevOps, CI/CD: Terraform, Ansible, G3, and SonarQube. - Cloud platforms: proven experience on at least one major public cloud (AWS, Azure, or GCP) in production-scale environments. - Security, compliance & risk controls: secure coding practices, threat modelling, encryption, key management, and OWASP mitigation patterns. ## Skills ### Required - Java - Spring - Kubernetes - Docker - Apache Kafka - Confluent - Spark - Flink - Delta Lake - Apache Atlas - LangGraph - Agent Development Kit - Microsoft Agent Framework - LangChain - LlamaIndex - Prometheus - Grafana - ELK/EFK - Jaeger - Zipkin - Terraform - Ansible - SonarQube - AWS - Azure - GCP ### Nice to have - Cloud certification - Kubernetes certification - Security certification - Data governance certification --- Source: [Apply at portal.careers.hsbc.com](https://portal.careers.hsbc.com/careers/job/563774608800937?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)