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.

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.

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 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.

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.

Build and own the cloud infrastructure for live AI-driven trading systems, using AWS, Kubernetes, Terraform, Python, Kafka, PostgreSQL, Redis, and ClickHouse. You will design deployment pipelines, multi-region environments, and observability with Grafana, Prometheus, and Loki. This is a founding engineering role, giving you direct ownership of the platform and architecture.

Man Group★3.6 (14)· London

Lead development of Man Group’s core Python compute platform, working with Kubernetes, Spark, Hadoop Yarn, Ray, and Airflow on Linux for systematic and discretionary investment strategies. You will build the research platform and APIs for researchers and developers.

Jump Trading★3.8 (11)· London

As a core development intern, you will design, code and test the firm's distributed trading system using C++ and Python on Linux, with Git for version control, and gain experience with Agile methodologies. The team builds and maintains Jump Trading's world-class low-latency trading platform and infrastructure.

AllianceBernstein★3.5 (269)· London

You will work with Python, SQL, Airflow, and Kubernetes, using the abAlphaLabs research platform for systematic strategies. The team develops, implements, and manages fully systematic, factor-driven fixed-income portfolios.

Tower Research Capital★4.1 (12)· London

You will support and maintain Tower Research Capital's Linux infrastructure for high-frequency, low-latency electronic trading systems, working with technologies including AWS (EC2, VPC, ELB, S3, EBS), Ansible, Python, Bash, Docker, and Kubernetes. Responsibilities include managing core services (DHCP, LDAP, DNS, NFS), automating provisioning and monitoring across thousands of servers in on-premises and cloud environments, and participating in on-call rotations supporting 24/7 critical trading infrastructure. You'll need at least five years of Linux administration experience, deep knowledge of OS internals and networking, and expertise in infrastructure automation and CI/CD practices.

JPMorgan★3.9 (20k)· London

You'll work with Python, KDB/C++, and AI technologies to design and optimize real-time data processing pipelines for JPMorgan's Electronic Trading Technology team within Commercial & Investment Bank. You'll lead technical initiatives across global analytics teams, building scalable solutions for mission-critical trading and research systems while mentoring engineers and driving SDLC improvements. This is a leadership role managing distributed teams in a fast-paced financial environment.

G-Research★3.6 (18)· London

You'll design and operate Kubernetes-based infrastructure using Go or Python to build custom operators, GitOps pipelines (ArgoCD, FluxCD), and Infrastructure as Code (Terraform, Helm), with strong observability via Prometheus and Grafana. The platform supports G-Research's quantitative finance operations, serving GPU-intensive machine learning and ultra-low-latency trading workloads while enforcing multi-tenant security with RBAC and OPA/Gatekeeper.

Tower Research Capital★4.1 (12)· London

You'll work with C++, Rust, Python, and large-scale build systems like Bazel, Buck2, and CMake to design developer tools, CI/CD pipelines, and infrastructure automation. Tower Research Capital is a quantitative trading firm where you'll partner across teams to enhance platform tooling, optimize build performance, and establish DevOps best practices for a high-performance electronic trading infrastructure.

You will develop production Python systems with SQL and modern databases to build data pipelines handling terabytes of exchange traffic in real-time for Maven Securities, a proprietary trading firm. The role involves designing analytics and data infrastructure supporting traders and quant researchers across discretionary, systematic, and market-making strategies in global listed derivatives. Ideal experience includes large-scale data engineering, streaming pipelines, containerization, C++, React/TypeScript, and financial markets knowledge.

Flow Traders, a proprietary trading firm, seeks a Senior Research Engineer to lead development of their trading model research framework using Python, PyTorch, Polars, Pandas, Ray, AWS/Azure/GCP, Docker, and Kubernetes. You'll design end-to-end ML pipelines for training and deploying trading models in production, then partner with Quantitative Researchers to develop data-driven systematic trading strategies and alpha signals.

You'll build cloud-native, high-throughput distributed systems for real-time market data processing using technologies like Kubernetes, Kafka, and modern data tools (Polars, Arrow, Flight/gRPC), with optional C++/Rust expertise. The Tick Data Platform team, newly formed and small, creates globally distributed market data architecture supporting QRT's quantitative research and trading operations. You'll collaborate with researchers and data scientists to architect scalable platforms from the ground up.

Man Group★3.6 (14)· London

Man Group seeks a Senior Systems Engineer to build and maintain infrastructure automation frameworks supporting global trading and research operations, working with Terraform, Ansible, Kubernetes, Python, Bash, PowerShell, Prometheus, Grafana, Jenkins, and CI/CD tools across Ubuntu and Windows Server environments at scale. The Platform Engineering team supports quantitative research and trading systems managing tens of thousands of cores and hundreds of terabytes of memory, creating self-service platforms for hundreds of users across the organization.