Retail Platform Principal Engineer

Provide strategic technical leadership across engineering projects, ensuring alignment with business goals, architecture principles and regulatory/compliance

. 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 Morden 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. Provide hands‑on technical direction: participate in design reviews, code reviews, prototyping and proof‑of‑concepts to validate architecture decisions. Collaborate with product, security, data and ops to align technical strategy with business objectives, regulatory requirements and non‑functional goals (scalability, resilience, security). Deliverables & Success Measures Architecture and platform designs that meet non‑functional requirements (scalability, resiliency, security). 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. 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. 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.