Python micro-services with RabbitMQ and OpenShift/Kubernetes, using SQL Server and Parquet. The London Commodities Risk Technology team builds a front-office distributed platform for trading and risk calculations on assets like oil, gas, power, and exotics, collaborating with traders and quants.

You will work with Python, JavaScript, SQL, Kafka, AWS/Azure, PostgreSQL, SQL Server, ClickHouse, and MongoDB. The team designs and delivers real-time, high-performance trading systems for Energy & Commodities, integrating market data, risk, and front-to-back office workflows.

Java (JDK 11+), multithreading, SQL/NoSQL databases (Oracle, MySQL, PostgreSQL, MongoDB, Cassandra), message queuing (Kafka, Tibco, Solace), Linux, JVM, and TDD. This tech lead role builds high-performance FX risk calculation systems for Citi’s Markets technology team, which supports global trading and risk management.

Use Python, Azure, Docker, Kubernetes, Apache Airflow, and GitHub Actions to build scalable ETL pipelines, financial data pipelines, and cloud-native infrastructure. This front-office role is at a systematic equity hedge fund modernising its quantitative research platform, working directly with portfolio managers and researchers. Experience with S&P Xpressfeed, Snowflake, Bloomberg, MSCI Barra, Databricks, and LLMs is advantageous.

Work as a Python software engineer on the Risk team, building and delivering solutions using Python, REST APIs, and modern software architecture with cloud platforms such as AWS, Kubernetes, Docker, or Helm. You will address requirements from the Risk Management team and Trading desks at a tech-driven quantitative and systematic investment manager.

You will work with Python, PowerShell, SQL, OMS/EMS platforms (FlexTrade, Triton, SpiderRock), Linux, Windows, cloud (AWS/Kubernetes), FIX, messaging systems, market data flows, and monitoring tools like Geneos/Zabbix. As part of a global hedge fund’s front-office technology team, you will directly support equity portfolio managers, traders, and analysts to ensure the reliability and performance of business-critical trading systems.

Work with Terraform, Ansible, Kubernetes, Python, Bash, Go, Jenkins, GitHub Actions, Prometheus, and Grafana to build infrastructure automation platforms supporting python-based quantitative research and trading systems. Manage on-premises resources across Ubuntu and Windows Server environments.

Builds cloud platforms for a systematic quant hedge fund's trading and research, using AWS (EC2, S3, VPC), Python/Bash, Jenkins/GitLab CI, Terraform/CloudFormation/AWS CDK, Docker, and Kubernetes to support digital asset and crypto systems.

Rebuild data infrastructure for a market-neutral systematic equities fund using Python, Microsoft Azure, Docker, Azure Kubernetes, Apache Airflow, and GitHub Actions for CI/CD. Work on ETL pipelines, vendor integration, and cloud-based research platforms, with relevant experience in Snowflake, Bloomberg, MSCI Barra, or Databricks. The role spans data engineering and quantitative development to transform financial data into investment signals.

You will work with Linux, AWS, Docker, Kubernetes, CI/CD pipelines, Python, Bash, and monitoring tools like Datadog, Prometheus, CloudWatch, or ELK. You will support and maintain the critical research and trading infrastructure for a quantitative hedge fund, acting as first-line support for platform-related issues.

You will build high-performance Java engines for algorithmic trading and liquidity seeking, and develop real-time trading desktops with React. Docker and Kubernetes experience is desirable. The team designs algo strategies and builds real-time systems for trading equity algo orders for Berenberg’s electronic trading expansion.

Backend engineers will use Java, Elixir, Scala, and TypeScript, plus Kubernetes, Docker, Linux, git, SQL, and Spark, to build compliance technology for a tech-driven proprietary trading firm. The team supports regulatory reporting and trade surveillance across global markets, with developers owning tasks end-to-end.

Lead the Credit Risk Analytics IT team using S&P Global FRA (fraimWRX), Redis, Kafka, Spark, HBASE, HDFS, Kubernetes, Python, .NET, C#, MS SQL Server, and MS Azure. The team designs, integrates, and supports systems for calculating and reporting Credit Risk across all locations. This is a VP-level role managing onshore, nearshore, and offshore developers.

You will work with Go and/or Python, plus Kubernetes, Docker, and cloud infrastructure. You'll support a systematic cryptocurrency trading team by maintaining live production trading and research systems, and helping to deploy strategies.

ExxonMobil★3.9 (5.7k)· London

Work as a Full Stack Developer using Python, Node.js, React or Angular, SQL/PostgreSQL/MongoDB, and cloud platforms like Azure/AWS/GCP. You will build and maintain scalable web applications, APIs, dashboards, databases, and data pipelines to support ExxonMobil's Global Trading organization's commercial and trading activities.

MUFG★3.3 (1k)· London

Works with S&P Global FRA, fraimWRX (AKS), Redis, Kafka, Spark, HBASE, HDFS, Kubernetes, Python, .NET, C#, MS SQL Server, MS Azure. Leads the Credit Risk Analytics IT team, designing and integrating Middle Office systems for calculating and reporting Credit Risk across all locations. Manages onshore, nearshore, and offshore teams.

Morgan McKinley★3.8 (45)· London

Core Java, Linux, low-latency messaging (FIX, SBE, Aeron, 29West), OMS, and performance profiling. The role designs and builds next-generation server-side crypto trading systems for a digital assets and data center infrastructure leader.

You will design, build, and operate AWS infrastructure, engineer Kubernetes environments (EKS, Docker, Helm), and use Terraform for infrastructure-as-code. You will support critical investment and trading systems, improve CI/CD pipelines with GitHub Actions and GitOps (Argo CD), and work with databases like Snowflake, Aurora, and SQL Server. You will take end-to-end ownership of production systems, solve complex problems across distributed environments, and influence cloud architecture and reliability standards.

Site Reliability Engineers will work with Python, cloud technologies, the Athena ecosystem (SecDB, Quartz), Linux, and Kubernetes. They will automate and re-engineer processes for the Market Risk Platform in a banking/finance/trading domain, using agentic AI to eliminate toil and improve reliability.

You'll work with Python (FastAPI), Postgres, Redis, Docker/Kubernetes, and AWS. As a founding London engineer, you'll own production services and build scalable backend systems for a commodity e-commerce and electronic trading platform provider.

Site Reliability Engineers will work with Python, cloud technologies, the Athena ecosystem, Linux, and Kubernetes, focusing on automation, optimization, and process re-engineering using AI for a Banking/Finance/Trading Market Risk Platform.

You will work with front-end technologies (HTML, CSS, JavaScript, React, Angular), back-end (Python, Node.js), databases (SQL, PostgreSQL, MongoDB), and cloud platforms (Azure, AWS, Google Cloud). You will design and maintain applications supporting commodity trading, market analysis, and risk management within ExxonMobil's Global Trading organization.

Use Python, Azure, Docker, Kubernetes, Apache Airflow, and GitHub Actions to modernize a systematic equity hedge fund’s quantitative research and engineering platform. You will build scalable ETL pipelines, cloud-native infrastructure, and research-ready datasets, working directly with portfolio managers and quantitative researchers.

ExxonMobil★3.9 (5.7k)· London

Full stack developer using React or Angular, Python or Node.js, SQL/PostgreSQL/MongoDB, and cloud platforms (Azure, AWS, Google Cloud). Builds and maintains web applications, APIs, and data pipelines supporting commodity trading, market analysis, and risk management within ExxonMobil’s Global Trading organization.

Senior C# .NET Developer working on high-performance applications for Global Markets IT. You will use C#, .NET, MS SQL, and DevOps/CI/CD tooling to build event-driven architectures supporting XVA, Liquidity and Financial Resource Management, collaborating with Front Office stakeholders.