You will build AI agents using Python, SQL, Docker, Kubernetes, AWS (RDS, EKS, S3), GitHub Actions, RAG pipelines, BM25, vector search, hybrid retrieval, and knowledge graphs. These agents interpret geopolitical and financial signals for Kharon, a company providing global security risk intelligence.

You'll use Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala to build high-performance, low-latency data systems. The Data Platform team in Global Markets owns the post-trade stack, processing high volumes of data and developing an AI-powered analytics UI/agent framework.

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.

Salesforce★4.2 (1.5k)· London

Success Architect works with Agentforce, Data Cloud, Salesforce Clouds, and data platforms like Snowflake, Databricks, AWS. They drive customer success by optimizing technical architecture for data unification and AI-driven automation, enabling personalized engagement and real-time decision-making.

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.

You will develop, maintain, and enhance Excel-based applications and add-ins using C#, .NET, Excel-DNA, VBA, SQL, and potentially Python. Working within a technology solutions team, you will support front-office investment teams (trading, research, portfolio management) by building tools that improve workflow automation, data access, and analytical capabilities.

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.

You'll develop systematic HFT and market-making strategies in cryptocurrency markets using Python for research, signal generation, backtesting, and live performance analysis. Working with your own firm's capital, you'll own the full research lifecycle—from hypothesis to production deployment—optimising execution quality, latency, inventory risk and spread capture across global exchanges.

You will work with AWS cloud data platforms including S3, Glue, and managed ETL services, using SQL and Python to design ETL/ELT solutions for extracting value from large-scale data. This role is for a Data Engineer at Third Nexus Group Limited.

EXL Service★3.7 (2k)· London

Design AI architectures on Azure using .NET, React, LLMs, RAG, OCR, and agentic frameworks (LangGraph, AutoGen, CrewAI) to build production-grade GenAI platforms. The role focuses on processing complex insurance documents for underwriting, claims, and reinsurance use cases. You will lead and mentor a team of .NET, React, and GenAI developers.

Design AI architectures on Azure using .NET, React, LLMs, Azure OpenAI, RAG, Agentic AI (LangGraph, AutoGen, CrewAI), OCR, microservices, and Azure AI Search. Build scalable GenAI platforms for intelligent automation in insurance functions like underwriting, claims, and reinsurance. Lead and mentor .NET, React, and GenAI developers.

JPMorgan★3.9 (20k)· London

You will work with Python, AWS, EKS, Docker, Kubernetes, Kafka, and MLOps tools. As a member of the Applied AI/ML Software Engineering team within CIB Security Services Technology, you will build cloud-based frameworks for hosting machine learning models alongside Data Scientists to integrate AIML solutions into production systems.

Capgemini★3.7 (11k)· London

Design, build, and manage data pipelines and models using AWS Snowflake, Azure Data Lake, Databricks, Redshift, and BigQuery. Automate CI/CD with Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD, and provision infrastructure with AWS CloudFormation, Docker, ECS, EKS, and Kubernetes. Capgemini is an AI-powered global business and technology transformation partner.

Build and ship AI features using LLMs, retrieval-augmented generation (RAG), and Python or .NET, deploying on Azure. You will join Shawbrook’s AI Engineering squad to move AI from proof-of-concept into production-grade systems supporting lending, deposits, operations, risk, and customer experience.

Design, build, and deploy LLM/RAG pipelines, agentic workflows, and backend APIs in Python on Azure. You will drive production-grade AI for lending, deposits, risk, and customer experience at Shawbrook Bank. Mentor other engineers in the AI Engineering squad.

Design, build, and deploy GenAI and ML solutions using OpenAI APIs, RAG, Python, Databricks, Spark, Delta Lake, and AWS (S3, Redshift, Lambda). You will work on predictive models and enterprise GenAI apps for Product, Sales, Finance, Marketing, Customer Success, and Engineering, owning projects end-to-end and integrating with Salesforce and Oracle platforms.

Design, build, and deploy quantitative models using Python, R, and libraries (numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot) plus NLP tools, SQL, AWS, Sagemaker, DataBricks, Snowflake, MLFlow, and Weights & Biases. The team creates systematic country risk analytics and ML/NLP pipelines for BMI’s market insights, supporting clients in risk assessment.

Work with Python, Azure, CI/CD, and LLM/RAG pipelines, including vector search and .NET. Build production-grade AI systems for lending, deposits, operations, risk, and customer experience in a regulated bank. Member of the AI Engineering squad.

You will work with Python or .NET, LLMs, retrieval-augmented generation (RAG), Azure, CI/CD, and APIs. The AI Engineering squad builds production-grade AI systems for lending, deposits, operations, risk, and customer experience at a bank.

Lead the development and operation of a large-scale AWS data platform using Redshift, S3, Glue, Lambda, Athena, EC2, Kinesis, Python, SQL, Bash, Spark, CI/CD, and DataOps. Provide senior technical leadership, mentor engineers, and oversee batch and streaming data pipelines for a major organisation.

You will use Python/PySpark, AWS S3/Glue/EMR, SageMaker, SQL, Git, CI/CD, Terraform/CDK, and Airflow/dbt/Step Functions to migrate ML data pipelines from Databricks (Spark/Delta Lake) to an AWS SageMaker MLOps platform. You join a small Databricks workstream team building and migrating feature engineering, feature store, and data access layers for production pipelines in a regulated iGaming environment.

Fitch Solutions★3.0 (2)· London

As a Data Scientist at BMI (a Fitch Solutions business), you will design, build, and deploy quantitative models using Python and R (e.g., numpy, pandas, scikit, pytorch) to power advanced analytics. You will develop and maintain ML/NLP and data pipelines, working with Economists and Analysts to build risk models and generate insights from structured and unstructured data.

You will work with Python, AWS (SageMaker, ECS, Lambda, S3, Glue), Terraform, FastAPI, Snowflake, SQL, GitHub Workflows, Grafana, and Metaplane. You will build and scale cloud-native infrastructure for ML, design CI/CD pipelines, and develop tooling for model deployment at a leading UK consumer technology business.

You'll work with Python, FastAPI, PostgreSQL, AWS services (RDS, S3, Redis, MongoDB), and AI-assisted development tools to design and optimize databases, build data-integration pipelines, and develop scalable APIs. The role owns the data layer powering M+C Saatchi World Services' platform, handling time-series, geospatial, and relational data across complex multi-source systems for a communications agency serving governments and international organizations. This is a full-time hybrid position in London, reporting to backend and data teams.