Full-stack Java development on Linux/Unix, using AI coding tools like Claude Code, Windsurf, Devin, or GitHub Copilot. The role is for Ascendion, a technology services company.

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.

Cint★3.5 (13)· London

Use Python and SQL for statistical modeling and machine learning to optimize Cint's programmatic research marketplace (Cint Exchange). You will analyze marketplace dynamics, conduct A/B tests, and build predictive models to guide product and pricing strategy.

You will build and evolve customer-facing interfaces for AI Virtual Agents using React, TypeScript, Next.js and Vite, and refactor the frontend into a scalable platform with a shared component library and design system. Unitary’s factory builds custom operations agents that complete complex workflows end-to-end in customer tools.

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.

DeepL★3.8 (4)· London

You'll work with C# / .NET, RESTful APIs, distributed architectures, and optionally React/TypeScript, plus MCP, CLIs, OAuth, and AI coding tools. You join the API Enterprise team, which builds enterprise adoption features (usage insights, cost controls, RBAC, compliance, data residency) for DeepL's Language AI API platform.

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.

FDJ UNITED★4.0 (96)· London

Build and maintain batch and streaming data pipelines on AWS using dbt, Spark, SQL, Kafka/Flink, and Airflow. Work on the Sportsbook Data Platform, a modern event-driven lakehouse transforming sportsbook data (bets, offers, etc.) into curated datasets for analytics, trading insight, and machine learning.

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.

Senior Software Engineer building a multimodal AI data fusion platform for Defence and Security using Python, distributed systems, container orchestration, and agent frameworks across cloud, edge, on-premise, and air-gapped environments. You'll design core platform components, develop AI orchestration systems, define deployment architectures, and influence technical direction across the organization. Requires 7+ years shipping production software, systems design expertise, and experience architecting multimodal data systems.

Work with SQL, Python, and modern data technologies (dbt, Spark, containers, DevOps tooling, orchestration tools, Git, AI/ML). As a Solution Engineer for the UK market, you present Snowflake’s technology and vision, working hands-on with prospects to demonstrate value through demos, proof-of-concepts, and design.

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 Microsoft Fabric, Databricks, Azure, Snowflake, Python, Spark, SQL/NoSQL, PowerShell, Azure Data Factory and Azure DevOps to build a Fabric Data Lakehouse for USS’s Investment Management business, implementing scalable ETL/ELT frameworks across a medallion architecture. Share knowledge across a small team of data engineers and collaborate with architects, business stakeholders and data teams.

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.

Quant developer role building equity portfolio analytics frameworks, including MSCI Barra factor risk models, using Python and/or R, SQL, and big data tools like Apache Spark. You'll design infrastructure for data extraction and transformation, liaising with portfolio managers and traders at a global hedge fund. Requires 5+ years' buy-side or sell-side experience.

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.

You will configure and maintain Workday, Greenhouse, CultureAmp, Kyriba, FloQast, and Workato, using Claude Code and agentic AI tooling. As an associate cross-platform engineer on the Finance & People Technology team, you support the SaaS estate underpinning finance and HR at a global alternative investment management firm.

You'll work with Python (Pandas, Arrow, Spark) and potentially Lakehouse tools (Delta Lake, Databricks, AWS). Joining Global Data Engineering, you provide first-line support for a high-frequency trading market maker, ensuring robust data pipelines and APIs for trading teams.

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.

Backend engineers will use Java, Elixir, Scala, and TypeScript, plus Kubernetes, Docker, Linux, git, SQL, and Spark, to build compliance technology for a tech-driven proprietary trading firm. The team supports regulatory reporting and trade surveillance across global markets, with developers owning tasks end-to-end.

You will use Python daily, with Ruby useful but not required, and AI tools like Claude in your workflow. The team focuses on greenfield projects in a start-up or small business environment.

Build and maintain scalable data pipelines (BigQuery, Cloud Composer, Airflow, Dataflow, Spark, Flink, dbt) on GCP for AI/ML experiences. Use Docker/k8s, Terraform, SQL, shell scripting, and monitoring tools (Monte Carlo, Looker, NewRelic, Splunk). Collaborate with product engineering, data science, and business teams.

SmartestEnergy★4.1 (15)· London

You will work with Microsoft Azure Data Platform, Microsoft Fabric, PySpark, SQL, Python, Azure DevOps, CI/CD, and Power BI to build enterprise-scale data pipelines and Data Lakehouse/Data Warehouse solutions. The team develops modern cloud-based data solutions supporting ETL/ELT processes across Medallion Architecture for SmartestEnergy’s energy digitisation and decarbonisation goals.

HCLTech★3.7 (11k)· London

Work with Quantexa Decision Intelligence Platform, Spark/PySpark, Python/Scala, and Big Data (Hive/HDFS) to design and develop data ingestion, transformation, and ETL pipelines. Focus on entity resolution, network analytics, and graph-based data models for analytics use cases.

Capital on Tap★3.9 (55)· London

First and foremost a software engineering role, you will work with C#, .NET, agentic systems and orchestration layers, and AI enablement tooling. You will build "AI on Tap", the company's internal hub for AI agents, and integrate agentic testing/verification across the pipeline to accelerate delivery for this financial platform.