Citi★3.9 (21k)· London

You will work with TypeScript, React, HTML5, CSS, JavaScript (ES6+), Chromium/Electron/OpenFin, FDC3, REST/WebSocket APIs, Kafka/Solace/Tibco, and CI/CD with Jenkins. The team delivers pricing solutions and trading GUIs for Citi’s Foreign Exchange business. You will provide technical leadership, mentor junior engineers, and drive AI integration.

Principal Data Engineer role using GCP, Python, Node.js, BigQuery SQL, and Jenkins CI/CD. The team enables Sky’s growth through Data and AI, deepening customer relationships, optimising commercial performance, and enhancing operational efficiency. The role provides technical leadership, managing Solution Architects and setting engineering standards.

MAREX★3.2 (6)· London

Risk Data Analyst at Marex works with the Data Platform, Power BI, and structured/unstructured datasets. The role bridges Risk and Technology, supporting data-led risk management, monitoring, and reporting across disciplines like market, credit, and operational risk.

Use Python, SQL, BM25, vector search, reranking, and RAG pipelines to evolve Kharon's Corestream risk intelligence feed—a platform surfacing entity-level insights and topic-based risk narratives, integrating graph-based outputs into semantic search and narrative generation.

Lead a team of Data Scientists and ML Engineers building AI solutions for financial markets using LLMs, Generative AI, Deep Learning, Transformers, Agentic AI, Python, PyTorch, TensorFlow, Hugging Face, LangChain, Semantic Kernel, Azure AI Foundry, AWS AI Services, and MLOps/LLMOps practices.

You will build AI agents using Python, SQL, Docker, Kubernetes, AWS (RDS, EKS, S3), GitHub Actions, RAG pipelines, BM25, vector search, hybrid retrieval, and knowledge graphs. These agents interpret geopolitical and financial signals for Kharon, a company providing global security risk intelligence.

Work with Python, SQL, BM25, vector search, reranking, RAG pipelines, agentic systems, and graph-aware search. Own and evolve Corestream, Kharon’s risk intelligence feed that surfaces entity-level insights and topic-based risk narratives for global security clients.

The technical lead will work with Java/J2EE, RESTful web services, Spring Boot, microservices, cloud technologies, Docker, Kubernetes, and CI/CD pipelines. They oversee architecture, design, and development of Java/J2EE applications, lead a team of developers, and drive technical excellence and best practices.

Infosys★3.8 (17k)· London

You will architect CI/CD pipelines using the Harness platform (CI, CD, STO, Chaos Engineering, CCM, AI Agents), Kubernetes, Terraform, Helm, OPA, and cloud services. As a Harness SME, you drive DevOps transformations, migrating enterprise teams from legacy tool chains and implementing DevSecOps governance.

Use Selenium, Playwright, Postman, JMeter, Jira, SQL, Git, Jenkins, and Azure DevOps to design and execute manual and automated tests. Validate merchant onboarding, payment processing, settlements, terminal management, and Lloyds Accept application flows across web, mobile (iOS/Android), and API systems.

Work with Python, LLMs, RAG pipelines, vector databases, Hugging Face Transformers, LangChain, PyTorch, and Docker to build production AI systems. Design, develop, and deploy AI-powered solutions such as conversational AI, document intelligence, and backend services for the Global Analytics team.

Lead a team of DataOps and MLOps engineers building and evolving the ML platform and data operations for FDJ United’s Sportsbook product. You’ll work with AWS, Terraform, CloudFormation, Spark, Kafka, and CI/CD pipelines to enable end-to-end machine learning workflows from research to production.

You will build scalable server-side logic using JavaScript, TypeScript, and Node.js in a microservices architecture on AWS with Kubernetes, Terraform, Kafka, and Snowflake. You will join the MMH team within the Martech domain, which orchestrates campaign delivery across email, push notifications, and personalised content for all Sainsbury’s Group brands. The team includes 7 engineers.

Lead an engineering team using Microsoft Power Platform, Power Apps, Dynamics 365, SharePoint, BizTalk, and Azure DevOps. Responsible for developing and delivering software applications, integrations, and services across the full product lifecycle for the British Red Cross.

Work with Azure (API Management, Logic Apps, Service Bus, Functions, Data Factory, Synapse), .NET/C#, PowerShell, SQL/NoSQL, and AI tools like GitHub Copilot. You will design and develop secure data integrations across the Azure middleware estate for the All England Lawn Tennis Club, which stages The Wimbledon Championships.

Develop backend services using Node.js, Python, Java, C#, PHP, and Ruby on Rails, with databases including MySQL,

TypeScript, React, Node.js, Bun, Kubernetes, and AWS. The team builds web apps, back-office systems, and tooling for financial product comparison across money.co.uk, Uswitch, and Confused. As a Staff Software Engineer, you set technical direction for Financial Services.

You will work with JavaScript (TypeScript), React, Redux, RX JS, NPM/Yarn, webpack, CSS, HTML, Azure DevOps CI/CD, and Java. As a senior developer on the FM Digital Channels team, you will build Blade, the bank's strategic in-house pricing, execution, and trade processing platform for Financial Markets.

You will work with Java, Git, Jira/ClickUp, and Agile Scrum. You own the server-side game logic for online slot games, implementing core mechanics, reel logic, and bonus flows, and coordinating with Game Mathematicians from concept to release.

Work with Java/Spring, React, JavaScript/TypeScript, CI/CD pipelines, and distributed systems. You'll join the Account Integrity team building a globally scalable fraud prevention engine to protect customer accounts and prevent financial crime using machine learning and real-time monitoring.

You'll use Python, SQL, shell scripting, containerization, infrastructure-as-code tools, and Scala/Java or Python to build and maintain scalable data pipelines. You'll support a financial technology company's data infrastructure, contributing to AI/ML experiences and international applications. No team size is stated.

Design, build, and operate a Kubernetes-based MLOps platform using Helm, Terraform, Kubeflow, KServe, vLLM, and JupyterHub. The platform supports the full model lifecycle—experimentation, deployment, and scalable inference—for AI, ML, and LLM workloads in production.

You'll build and operate a Kubernetes-based AI/ML platform using Helm, Terraform, Kubeflow, KServe, vLLM, and JupyterHub. This role focuses on creating infrastructure, tooling, and guardrails so MLOps and data science teams can reliably deploy and serve models at scale.

You will work with AWS, Python, SQL, ETL/ELT pipelines, data warehousing, and APIs. You will own the data platform for a company developing AI and machine learning products that help enterprise clients make decisions. You will start as a senior individual contributor with the opportunity to build and lead a future data team.