Google★4.3 (6.2k)· London

Manage engineers building Google’s Learning Platforms within the Global Business Organization, which powers Google’s ecosystem of products and services for customers and partners. Work with back-end languages (Java, Python, Golang, C++) and front-end (JavaScript, TypeScript, HTML, CSS), plus ML model fine-tuning and evaluation.

This role develops generative AI applications using Java, Python, React or Angular, LangChain, LlamaIndex, Hugging Face, Docker, Kubernetes, and AWS, with tools like GitHub Copilot. You will build scalable, AI-powered solutions for Citi’s global finance operations.

Work with LLMs and vision models, fine-tuning, prompt engineering, and TypeScript. Develop and refine core models powering automated AML and KYC workflows for a YC S24-backed startup automating financial crime compliance.

Citi★3.9 (21k)· London

Build and scale AI-powered financial systems using Java, Spring, React/Angular, Python, FastAPI, Docker, and GitHub Copilot within Citi’s global tech environment. You will design generative AI agents, LLM workflows, and RAG pipelines while working on enterprise microservices, mobile, or front-end development. This role is for an individual contributor on an agile team.

You'll develop Conveo's AI-powered consumer and B2B research platform using React, TypeScript, Node.js, PostgreSQL, and AWS/GCP infrastructure, with exposure to LLM APIs and prompt engineering. The role spans full-stack development—from API design to frontend implementation—plus direct customer interaction to translate research needs into technical solutions. You'll work autonomously on feature ownership within a small, high-performing engineering team at this Y Combinator-backed startup.

Work with Python, TypeScript, LLMs, RAG pipelines, agent architectures, MCP, eval frameworks, CI/CD, and cloud (AWS/GCP preferred). You will join a small pod to deliver end-to-end AI client engagements—building prototypes, MVPs, and integrating into enterprise environments.

Fitch Ratings★3.8 (136)· London

You'll build ML/AI solutions using Python, FastAPI, PyTorch/TensorFlow, LangChain, LangGraph, and React/TypeScript within cloud-based microservices architectures. The agile team delivers software products for Fitch's BMI business, which provides data-driven market insights and risk analysis to customers globally. You'll design full-stack enterprise applications, implement GenAI features with LLM integration, and establish development best practices across the product suite.

Deloitte★3.9 (14k)· London

You will work with Python, JavaScript, Kafka, Azure, Kubernetes, Terraform, Helm, LangChain, PySpark, Databricks, and ADLS. You will design, develop, and deploy production-grade GenAI and machine learning systems for the GenAI team within Deloitte’s Data & AI organisation.

You'll work with MCP, Python, TypeScript/Node, React, SQL, and UI protocols (A2UI, AG-UI, MCP-UI) to build agent loops, orchestration, and generative UI. The role owns AI capabilities end-to-end for commercetools' autonomous commerce platform, taking capabilities from prompt to production.

Checkout.com★3.8 (15)· London

You will work with LLMs (GPT, BERT, Llama, Gemini), Python/JavaScript, AI frameworks (LangChain, PydanticAI), cloud platforms (AWS/GCP/Azure), Docker, Kubernetes, and Terraform. As part of Checkout.com’s AI Centre of Excellence, you will design, build, and deploy Generative AI solutions (chatbots, assistants, knowledge extraction tools) to enhance products and streamline business processes.

You'll work with Python (FastAPI), Go, TypeScript, PostgreSQL, Redis, Pinecone/pgvector, AWS (ECS, Lambda, SQS), Docker, Kubernetes, Terraform, LangChain/LlamaIndex, vLLM, and Anthropic/OpenAI APIs. You'll build and optimize RAG pipelines, real-time inference APIs, and vector search infrastructure powering LLM features for 500k+ monthly active users.

WTW★3.6 (1.7k)· London

The Data Engineer will work with Microsoft Fabric, Azure Synapse, Azure Data Factory, PySpark, Python, Power Automate, and Copilot/AI tools to design, build, and optimize data pipelines. They will integrate AI/LLM models and Power Platform automation into data workflows, collaborating with data experts and business teams.

You'll use React, TypeScript, and C# (or comparable OO language) to build customer-facing experiences and backend systems. Own features end-to-end across OAG Digital's Core platform (auth, entitlements, billing) and Intelligence layer (AI-powered insights on Databricks and Snowflake).

9fin★0.0· London

You'll work with Python, TypeScript, Docker, Kubernetes, AWS Bedrock, RAG, MCP, and observability tools like Arize Phoenix. The AI Engineering team builds the core platform for Generative AI, Agentic AI, and ML applications powering debt market products. You'll be one of a few senior engineers shaping the platform's architecture with the Engineering Lead.

Zoopla★3.9 (18)· London

Work with Python, scikit-learn, PyTorch, TensorFlow, AWS (SageMaker, ECS, Lambda, SQS, DynamoDB), and MLOps tooling to build end-to-end ML pipelines. You will design and deploy production ML models that bring intelligent automation and predictive capability to the UK property market, using Alto's large dataset of real housing transactions.

Ebury★3.3 (13)· London

You will work with React, TypeScript, Python, FastAPI, Strands Agents SDK, AWS Bedrock, RAG, Ragas, Langfuse, AWS/GCP, Terraform, and Docker. You will build Flow, an internal AI agent platform that orchestrates multi-step workflows across data warehouses and services to automate business operations. The role involves end-to-end ownership of agent workflows, reasoning UIs, and cross-system integrations.

Depop★4.4 (61)· London

PyTorch, large language models (LLMs), Transformers, Python, and MLOps tools. The role designs and builds scalable ML systems to detect fraud, abuse, and policy violations in user-generated content on a peer-to-peer circular fashion marketplace.

Cint★3.5 (13)· London

Working with Large Language Models (LLMs), Python, SQL, and frameworks for LLM development, fine-tuning, and Prompt Engineering/RAG. You will build next-generation AI solutions that bridge traditional research data and synthetic intelligence, developing models for synthetic row generation, open-ended text generation, and data augmentation within Cint’s programmatic research marketplace.

Work with Python/TypeScript, FastAPI/Flask/Express/NestJS, AWS/Azure/GCP, Kubernetes/Docker, Terraform, PostgreSQL/DynamoDB, and CI/CD tools. You will build core infrastructure for the Scale Generative AI Platform (SGP), designing scalable APIs, distributed data systems, and deployment pipelines for enterprise GenAI production

You will work with Python, TypeScript/JavaScript, Java, or C++ and cloud platforms (AWS, GCP, Azure) to build and deploy end-to-end generative and agentic AI applications, create training datasets, and design evaluation pipelines for LLMs. The Global Public Sector team builds custom AI applications for government clients, impacting millions of citizens.

Ebury★3.3 (13)· London

Build an AI-powered financial crime investigation platform using React, TypeScript, FastAPI, Python, LangGraph, LlamaIndex, and AWS (Bedrock, ECS, DynamoDB, OpenSearch). Design AI agent workflows and micro-frontend architecture while mentoring engineers.

Elliptic★0.0· London

You'll design and build agentic workflows using LangChain or LangGraph, develop backend services in TypeScript and Node.js, and create evaluation frameworks for LLM outputs. Elliptic builds AI-powered compliance tools that help investigators trace blockchain fund flows and detect financial crime. You'll lead the AI team's technical direction, mentor junior engineers, and own significant features from design through production.

Build and maintain scalable backend data services using Python, FastAPI, SQL, Docker, Kubernetes, and CI/CD pipelines. You’ll work on the Signal Ocean platform—an AI-driven intelligence system for shipping and commodities—within the Modelling & Data Services team, collaborating with data science and product.

You'll work with TypeScript, Node, React, PostgreSQL, GraphQL, Temporal, MCP, and GCP to build Ravio's agentic compensation platform—moving from a traditional SaaS to a system of parent and specialist agents, durable workflows, and an eval harness. As a hands-on individual contributor, you will own architecture across the customer-facing web app, agentic platform, and shared infrastructure.

You’ll work with Python/TypeScript, FastAPI/Flask/Express/NestJS, AWS/Azure/GCP, Kubernetes, Docker, Terraform, PostgreSQL, and DynamoDB. You’ll build backend infrastructure for Scale’s Generative AI Platform, delivering APIs and distributed systems that bring GenAI into production for large enterprises.