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.

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.

Work with Microsoft Azure data platforms: Azure Synapse, Azure SQL Server, Azure Data Factory, Azure DevOps, Microsoft Fabric, and OneLake; also uses DBT and Spark. You will modernize core data platforms—ingesting data from MS Dynamics CRM, Finance & Operations, and SAP SuccessFactors—to power analytics, AI-driven insights, and executive decision-making.

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.

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.

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.

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.

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.

You will work with Microsoft Power BI (including composite models over Azure Analysis Services), Snowflake, Power Automate, and SQL. You will build and maintain the reporting estate supporting INEOS Automotive's global sales, retailer, and customer experience operations.

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.

Design and build production-grade ML systems using MCP servers, recommendation systems, RAG pipelines, LLMs, and foundation models with Python, TensorFlow, PyTorch, FastAPI, and LangChain. You will own the end-to-end AI lifecycle for a sales data platform, deploying models into batch/real-time environments to drive forecasting, segmentation, and early warning systems. This role focuses on embedding context-aware intelligence into decision-making tools for business stakeholders.

You will work with Databricks, Microsoft Fabric, Power BI, SQL, Python, and modern lakehouse architectures. This role leads delivery of business-critical analytics used by hundreds of stakeholders globally, architecting scalable data solutions and enabling strategic decision-making across Finance, Commercial, and Operations.

Work with Python, SQL, AWS, ETL pipelines, data lakes, and enterprise integration tools. You will own legacy data pipelines, ingestion, and integration for a VC-backed AI startup building software for a safety-critical sector, handling fragmented real-world infrastructure from backend systems to warehouse and schema design.

FDM Group★2.9 (270)· London

You'll work with Python, pandas, JSON, REST APIs, LLMs, RAG, vector embeddings, and semantic search to build data ingestion pipelines and scalable platforms that enable AI-powered analytics and decision support within a leading global investment bank.

Work with Python, Pandas, NumPy, Polars, Flask/FastAPI, and optionally Databricks and AWS. You will build scalable tools for the Risk Division in an energy commodities trading environment, supporting traders and risk analysts by centralising data and improving reporting.

You will work with Microsoft Power BI (including composite models over Azure Analysis Services), Snowflake, Power Automate, and SQL. As part of Global Sales Operations, you will build and maintain dashboards supporting INEOS Automotive’s global sales, retailer, and customer experience operations.

You'll work with Microsoft Power BI (including composite models over Azure Analysis Services), Snowflake, and Power Automate. Your role builds and maintains reporting dashboards for global sales, retailer, and customer experience operations at INEOS Automotive.

You will architect and scale backend services using Python, FastAPI, and PostgreSQL, and work with message brokers like Azure Service Bus, RabbitMQ, or Kafka, plus Celery, Docker, and Kubernetes. The company builds an AI workspace processing sensitive financial data for large banks and regulated institutions under SOC 2, GDPR, and FCA compliance. You will report directly to the founders on a senior, staff-track IC team.

You will design and build Python services and APIs using AWS (Lambda, S3, ECS/EKS, Step Functions, Aurora), Kafka, and PostgreSQL/SQL Server/Snowflake to support portfolio construction, trading, and analytics. This Investment Technology role turns research tools into production-grade platforms for Portfolio Managers and Quantitative Researchers across Equities, Fixed Income, and Alternatives.

Design and develop AI agents using AWS AgentCore, Amazon Bedrock, Python, and TypeScript. Build backend services with AWS Lambda, API Gateway, Step Functions, DynamoDB, and IaC tools like Terraform or AWS CDK for enterprise multi-agent workflows and production monitoring.

You'll use Python (with Pandas, NumPy, Polars, Flask/FastAPI) to build scalable tools and a platform for the Risk Division in energy trading. AWS cloud deployment is a plus.