6 of 6 Remote/Hybrid Event-Driven Architecture Jobs in Central London

take an active role in practice development: developing new data services to help with our client' business development creating and updating data architecture artefacts, liaising with other our client practices to maintain practice profile and contributing to the development of more junior practice members. In addition to technical … least one programming language such as Python, Scala, or Java. ETL/ELT design and data pipeline orchestration. Streaming and event-driven data architectures. Agile and DevOps delivery methodologies applied to data platforms (DataOps). Expertise in data architecture and modelling (conceptual, logical ...

develop backend applications and services within a Java environment. Build and enhance distributed systems operating at high throughput and availability. Design event-driven architectures and integrations using Kafka. Shape technical approaches and contribute to architecture and engineering standards. Lead technical design discussions and drive … production environments. Deep hands-on Java development experience. Strong understanding of distributed systems and scalable application design. Strong experience with Kafka and event-driven architectures. Experience designing microservices, APIs and integration patterns. Strong Kubernetes experience within production environments. Good understanding of software architecture, design ...

experience with Databricks, Spark, SQL, and Python Experience developing and optimizing batch and real-time data processing solutions Strong understanding of modern data architecture patterns, including Kimball, Data Vault, dimensional modelling, and data product design principles Experience implementing Infrastructure as Code using tools such as Terraform or CloudFormation … Experience Experience delivering Financial Services, Wealth Management, Asset Management, or Investment platform data solutions Experience working with AWS-native data services and event-driven architectures Experience building data products that support analytics, reporting, machine learning, or AI use cases Knowledge of MLOps, AI Engineering, Agentic ...

trading platforms. The organisation is investing significantly in its technology capabilities, evolving from a predominantly Microsoft-based environment towards a modern, cloud-enabled architecture incorporating C#, .NET Core, Java, AWS, Kafka and Redis . The successful candidate will combine strong hands-on engineering expertise with the ability … involving application modernisation or cloud-native development. Modern .NET/.NET Core. Java development experience alongside C#. Distributed systems, Kafka, Redis or event-driven architectures. Experience developing applications supporting OTC derivatives or complex trade lifecycle processing. Practical experience using AI-assisted engineering tools such as GitHub ...

exciting opportunity to shape production-ready agentic AI systems, combining intelligent automation with scalable cloud technology. You'll take ownership of AI architecture and implementation, designing multi-agent workflows, retrieval-augmented generation (RAG) solutions and AI microservices. Working closely with architects and product teams, you'll turn business … tool integration Azure AI Search and RAG architecture Multi-agent systems and orchestration workflows Vector databases, embeddings and semantic search Event-driven architectures and REST APIs Docker, Kubernetes and AI microservices MLOps/LLMOps, AI governance and production troubleshooting Location: London, UK - hybrid working ...

business processes through Salesforce Data Cloud and wider integration platforms. Build integrations using REST/SOAP APIs, MuleSoft, Platform Events and event-driven architecture. Apply prompt engineering, retrieval-augmented generation (RAG), grounding and techniques to reduce AI hallucinations. Test and evaluate AI solutions for accuracy, quality … engineering, RAG, grounding and AI evaluation. Experience working with Salesforce Data Cloud and enterprise data integration. Knowledge of APIs, integration patterns and event-driven architecture. Strong software engineering fundamentals, including debugging, testing, code quality and version control. Confidence explaining technical decisions, solving complex problems and working ...