Use object-oriented programming (Java or C#), Salesforce Lightning, Force.com, Apex, SOQL, JavaScript, Git, Jira, IntelliJ, CI/CD, and Salesforce REST APIs. Hackajob Ltd is a platform that connects developers with job opportunities. This Salesforce Developer role delivers complex business and technical requirements on the Force.com platform.

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.

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.

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.

You'll work with PyTorch, TensorFlow, XGBoost, GPUs, CI/CD and containerisation on the Search & Recommendations team, building production-grade ML systems for personalised recommendations, product ranking and AI-driven styling at ASOS, covering the full lifecycle from experimentation to deployment.

Wise★3.5 (42)· London

You will build and refine financial crime prevention systems using Java (or JVM languages) with Spring, React/JavaScript/TypeScript, and CI/CD pipelines, working 80% backend and 20% frontend. You join the Account Integrity team, which protects Wise’s global platform against fraud via machine learning and real-time transaction monitoring, and you will own projects end-to-end.

Native Kotlin and Jetpack Compose development on a consumer-facing Android app for in-store grocery trips, running on a known device inside live stores. Integrates on-device edge AI (ML Kit, TensorFlow Lite) and uses AI coding tools like Cursor or Claude Code. Reports to the Head of Android.

Senior Machine Learning Engineer at ASOS, building production ML systems for personalized outfit recommendations and style discovery. You'll work with deep learning frameworks like PyTorch/TensorFlow, distributed GPU infrastructure, and MLOps practices including CI/CD, containerization, and observability. Collaborate with ML Scientists on batch and real-time models serving millions of customers.

You will own the dbt project (models, tests, CI/CD) and work with BigQuery (or Snowflake/Redshift), advanced SQL, and a BI tool like Looker or Metabase. As an Analytics Engineer for a £100m+ D2C e-commerce brand, you'll transform raw data into trusted dashboards that drive marketing, finance, and operational decisions.

Work with Java, Python, JavaScript/TypeScript, Go, cloud platforms (AWS, Azure, GCP), CI/CD pipelines, and version control. Guiding the technical direction of BabuSpace’s premium short-term rental marketplace platform for African cities, designing backend architectures, and mentoring engineers.

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.

Design, build and optimise ETL data pipelines using Databricks, PySpark, Python, and SQL for a leading global investment bank. You will work on large-scale enterprise data platforms in a fast-paced financial services environment.

This DevOps traineeship covers Linux, Git, Docker, container orchestration, AWS, Azure, Google Cloud, CI/CD, shell scripting, IaC, configuration management, monitoring, networking, and DevSecOps. It provides hands-on experience through realistic projects such as building CI/CD pipelines, deploying applications, managing containers, and automating processes, with no prior experience required.

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.

A Senior AI Engineer at Stakemate will use agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG, Python, cloud services (Azure/GCP/AWS), and SQL to move AI from experiments to production. They will shape the platform and architecture for a live betting product at a fast-growing social sports betting startup.

Build enterprise-grade web applications using Python (Django/FastAPI), React, TypeScript, and PostgreSQL. Develop RESTful APIs, responsive UI components, and contribute to system design, CI/CD pipelines, and performance optimization.

Microsoft★4.2 (9k)· London

Work with AI and cloud platforms such as Azure ML and OpenAI, applying practices including prompt engineering, retrieval-augmented approaches, model tuning, and CI/CD tooling. As a member of the Frontier Company Engineering team, you will embed within customer teams to build production-ready systems and services that solve complex organizational challenges.

You'll work with React and TypeScript to build frontend interfaces for Digital Asset's Financial Engineering team, which designs mission-critical financial workflows like Asset Tokenization and Collateral Management on the Canton Network blockchain. The role involves UI architecture, design systems, performance optimization, and backend integration while collaborating with product and design teams across hybrid locations in Switzerland, UK, Hungary, or Hong Kong.

You will work with agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG pipelines, vector stores, Python, SQL, and a major cloud (Azure AI Foundry, GCP, or AWS). You will take AI agents from proof-of-concept to production within Stakemate’s live sports betting product, setting the governance and standards for the company’s AI estate. Reporting to the CTO, you will shape the platform and architecture as the company scales.

You’ll work with Python (Django/FastAPI), React, TypeScript, PostgreSQL, REST APIs, and CI/CD. You’ll own end-to-end feature delivery on scalable, enterprise-grade web applications.

Develop core eTrading MI & Analytics platform components using q and kdb+, with CI/CD, TDD/BDD, and an additional programming language. The platform captures, stores, and analyses over 3TB/5 billion daily records from electronic trading venues for risk, quant, trading, and sales stakeholders.

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.