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.

Lead Python Developer role using Core Python, Flask, VueJS, JavaScript, CSS, HTML, SQL, AWS, Terraform, Docker, and serverless components, with CI/CD and Agile practices. The developer builds, enhances, and supports production applications within UK public sector programmes, collaborating with delivery, product, and data teams.

Trainees will learn Linux, Git, Docker, AWS, Azure, Google Cloud, CI/CD, and Infrastructure as Code. The program provides structured training and practical DevOps projects to build a portfolio. No prior experience is required.

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.

Work with Python, FastAPI, Docker, DuckDB, JSON Schema and Git to design, build and ship client ETL pipelines that map raw bank data onto the FIRE regulatory reporting standard. You will maintain a shared ETL framework, write validated mapping code, and mentor junior engineers at Suade, a regtech SaaS company automating compliance for financial institutions.

BNY★3.5 (5.5k)· London

You'll use Java 17/21 with Spring, Maven, Groovy, JavaScript/TypeScript (Angular), Docker, GitLab CI/CD, IntelliJ, Windsurf, Splunk, and AppDynamics to build secure backend services, batches, and APIs for a global financial services company.

Zoopla★3.9 (18)· London

A 12-month maternity cover role on a dual-stack C#, .NET, and TypeScript backend with React microfrontends, using AWS managed services (ECS/Fargate, Lambda, SQS, DynamoDB, DocumentDB) and Terraform/SST. You'll build B2B SaaS software for estate agents and home builders at Alto Software Group. Take end-to-end ownership of features from design to production, working with the product team and AI coding agents.

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.

Backend engineers use Python, Django, Django-REST-framework, GraphQL (Graphene), Celery, Postgres, and AWS (Packer, Consul, Terraform). They build and maintain the AI-driven energy management platform that powers utilities and optimises renewable generation. The global engineering team is around 1,400 people.

FDJ UNITED★4.0 (96)· London

You'll lead a DataOps/MLOps team building an ML platform and data operations capability for FDJ United's Sportsbook, working with AWS, Terraform/CloudFormation, Spark, Kafka, and CI/CD pipelines for end-to-end ML lifecycle management. The role involves establishing best practices, monitoring, and governance while collaborating with Data Engineering, ML Engineering, Quants, and Data Science teams to personalize customer experiences and manage risk.

You'll design and own end-to-end RAG pipelines for payments domain content using Python, Azure Data Factory, Functions, ADLS, CosmosDB, and AI Search, with CI/CD via GitHub Actions and Azure DevOps. RedCompass Labs builds AI-powered payment transformation and financial crime detection solutions, including the RedFlag Accelerator for identifying human trafficking. You'll collaborate with AI engineers and payments experts to turn regulatory documents and handbooks into a reliable retrieval layer for their proprietary multi-agent AI platform.

You will work with Java and SpringBoot microservices on Linux and OpenShift, building APIs and using build tools like Gradle, CI/CD, Git, and BitBucket/GitHub. As part of the Technology Application Strategy team, you will design and deploy cutting-edge developer tooling and productivity solutions for Citi’s global developer community.

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 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.