Citi★3.9 (21k)· London

Backend Java developer building the Citi Integrated Digital Assets Platform (CIDAP) using Java Spring, web3 libraries (Web3J/Web3JS), Solidity, and containerized DevOps tools (Git, Jenkins, Helm).

Citi★3.9 (21k)· London

You will work with Java, Spring, Web3J/Web3JS, Solidity, Docker, and Hardhat/Foundry to build Citi’s Integrated Digital Assets Platform (CIDAP), integrating blockchain networks and digital asset infrastructure.

Citi★3.9 (21k)· London

Work with Solidity, Web3J/Web3JS/Ethers.js/Viem, Java/Spring, Node.js, and blockchains such as Ethereum, Hyperledger Besu, Canton, and Solana, using Hardhat/Foundry/Truffle for testing. Contribute to Citi's Integrated Digital Assets Platform (CIDAP) building Web3 components for tokenization, smart contracts, and on-chain settlement.

You will work with Python, AI coding agents (e.g., Claude Code, Codex), and potentially AWS, Kubernetes, and Temporal. Unitary builds Virtual Agents — AI-powered software workers that automate complex workflows end-to-end in customer tools, focusing on commercial insurance, marketplaces, and primary healthcare.

Lovable★4.0 (43)· London

Uses Go, Rust, TypeScript; AWS, Azure, Google Cloud, Cloudflare; Kubernetes, Terraform, Temporal, OTEL, CI/CD; PostgreSQL, ClickHouse, Firestore, Spanner, BigQuery. Builds the platform for Lovable Enterprise enabling secure, cloud-agnostic deployment, defining architecture for sandboxing, networking, encryption, identity, and mentoring engineers.

Citi★3.9 (21k)· London

Build index‑calculation platform components at Citi using Scala and Python, integrating via REST APIs and Solace message queues, and working with Couchbase (NoSQL), Gradle, Jenkins, Tekton, and OpenShift. The SolstiCE team supports the Citi Investment Strategies (CIS) engineering group by developing and maintaining an index calculation platform for the Equity Derivatives Tech business.

Checkout.com★3.8 (15)· London

Senior Engineering Manager leading the Disputes team, which builds tools, services, and machine learning models to help merchants manage and win chargeback disputes at scale. The team owns a full stack centered on .NET / C#, React and TypeScript front ends, Python-based ML, and event-driven microservice architectures.

DeepL★3.8 (4)· London

Work with Kubernetes, Terraform, ArgoCD, Go or Python, and AWS across hybrid on-prem and cloud infrastructure. The Hybrid Platform Engineering track builds and operates the compute layer—Kubernetes control plane, networking, storage, and core services—powering DeepL's language AI products and research. The role involves deepening the hybrid model and unifying workloads across on-prem and AWS.

Design, implement and maintain CI/CD pipelines, deploying and managing cloud infrastructure on AWS and/or Azure with Kubernetes. This role is with Closing Gap, a network placing DevOps engineers into enterprise-scale environments at leading UK technology organisations.

Principal C#/.NET engineer leading solution design and hands-on development using C#, .NET Core, MongoDB, SQL Server, Kafka/ActiveMQ, and OpenShift/Kubernetes. Mentors developers and directs engineering, applying SOLID, microservices, and contract-first API design within a regulated financial services environment.

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.

You’ll work with modern C++, Python, and systems-level knowledge of CPU, memory, OS, and networking. As part of a trading-desk Quant Dev team collaborating with researchers and traders, you’ll build ultra-low-latency trading engines, research platforms handling terabytes of daily data, and cloud-based analytics infrastructure for a global systematic hedge fund.

Java 11+, Spring Boot, microservices, event-driven architecture, Terraform, and cloud platforms (Azure, AWS, or GCP). The team builds post-trade technology solutions including business-critical applications, APIs, client reporting platforms, and web portals for capital markets. You will mentor developers and contribute to architectural decisions.

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.

Work with Java, GitHub Copilot, Devin.AI, Citi Squad, Stylus Workspaces (Gemini, OpenAI, Claude, Llama), Docker, Kubernetes, and CI/CD. Build high-performance, real-time FX risk management systems for a greenfield platform with a 10+ year strategic commitment. As a VP, lead end-to-end delivery and technical direction.

Work with AWS, Kubernetes, Terraform, Python, and IaC tools. Build and scale a critical AWS platform used across a bank, improving platform stability through new technology and processes.

Lead DevOps Engineer: work with AWS, Azure, GCP, Terraform, Linux/Unix, Python/Go/PowerShell/Nodejs/C#, and CI/CD tools (Octopus/TeamCity/Jenkins/Azure DevOps). Role is at a tech consultancy building and running cloud infrastructure, automating deployments with IaC, and managing a team of engineers.

You will work with AWS, Kubernetes, Terraform, Python, Java or Scala, and AI-driven development tools (Claude, LLMs). You will build and maintain the distributed-compute and data-science platform that powers Macquarie's trading and analytics workflows, collaborating with quantitative analysts and trading desks.

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.