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.

Python, FastAPI, Docker, DuckDB (nice-to-have), JSON Schema, Git, and RESTful APIs. You will design and ship ETL pipelines that transform raw bank data into the FIRE regulatory reporting standard. Suade is a regtech SaaS company automating compliance and risk solutions for financial institutions.

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.

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.

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.

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.

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.

Working with Core Python, Pandas, NumPy, Flask/FastAPI/Django, SQL, and Unix/Linux, you will build backend applications and data processing pipelines for trading and risk management within an investment banking environment, supporting risk calculations, trade workflows, and reporting.

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.

HSBC★4.0 (16k)· London

Work with Python, Docker, Kubernetes, Flask/FastAPI, PyTorch/TensorFlow, SQL Server/Postgres, and CI/CD pipelines to build and deploy production-grade ML and GenAI services. You will join the Growth AI programme within HSBC’s Corporate & Institutional Banking Data & Analytics, developing AI applications to identify business opportunities and mitigate client attrition.

Edited★2.7 (3)· London

You will work with Python, *nix, LLMs, MCP, Django, Flask, FastAPI, Elasticsearch, and SQL databases. You will build an AI chatbot with agents and tooling, and scale a large-scale retail data infrastructure on AWS and bare metal for the company's AI-driven retail intelligence platform.

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.

EXL Service★3.7 (2k)· London

You will work with Python, FastAPI, LLM frameworks (prompt engineering, RAG, agentic systems), and cloud AI platforms (Azure OpenAI/AWS Bedrock/Claude) on Kubernetes. As a Sr. AI Architect & Client Partner at EXL, a data and AI services company, you will design and deliver production-grade Generative and Agentic AI systems for enterprise clients, converting ambiguous mandates into secure, scalable solutions while shaping deals and reusable IP.

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.

Senior Python Developer role building trading and risk platforms using Python, SQL, Pandas, NumPy, Flask/FastAPI/Django, PySpark, Unix/Linux shell scripting, and enterprise platforms like Quartz or SecDB. The team develops backend services, data pipelines, and risk applications for trade lifecycle, risk calculations, and regulatory reporting within investment banking.

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.

Senior Software Engineer building and operating systems that move and safeguard cryptoassets—treasury automation, wallet inventory, custody integrations, and operational controls. Work with Python (FastAPI), Kubernetes, CI/CD, GitOps, relational data modeling, and job orchestration tools (Airflow, Prefect).

You will use Python with Pandas, NumPy, and FastAPI/Flask to build backend services and APIs. You will also work with SQL, Linux/Unix, and risk analytics platforms to support trading, risk analysis, and trade processing for the front office.

Wise★3.5 (42)· London

Build backend

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.