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.

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.

Goldman Sachs★3.9 (2.3k)· London

Build a high-performance, low-latency data platform for post-trade processing using Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala. You will own the full lifecycle of core systems, designing distributed computation and an AI-powered UI/agent framework to deliver intelligent analytics over large-scale business data.

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.

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.

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.

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.

Virtusa★3.7 (1.1k)· London

Work with Snowflake, DBT, Python, SQL, and AWS services to build enterprise data platforms. The role supports a global pharma engagement, designing scalable data solutions for advanced analytics, clinical insights, and business intelligence.

Snowflake, DBT, Python, SQL, and AWS. Leads architecture of enterprise data platforms for a global pharma engagement supporting clinical insights, business intelligence, and data governance.

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.

Java back-end developer using microservices, REST APIs, AWS (Lambda, EKS, RDS, S3, MSK), CI/CD, and AI tools (GitHub Copilot, LLMs). Builds next-gen trading and cash management systems for the Short-Term, Cash, and Collateral desks, modernizing platforms and migrating to AWS.

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.

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.

Work with C#, Python, Java, SQL, and AWS (ECS, S3, DynamoDB) to design, build, and maintain TradingHub’s market data environment and analytics. Collaborate with Pricing Quants and Risk Strats to productionise financial markets data for the company’s trade surveillance software.