You will work with Python, LLMs, agentic workflows, retrieval-augmented generation (RAG), and internal AI platforms. The Tactical AI Automations team deploys and supports AI tools across PIMCO's Portfolio Management and Analytics groups, including operational support for Lane Assist and POET (portfolio optimization tools).

Work with Azure, Terraform, Azure DevOps, container platforms, and AI agents to build and automate cloud infrastructure. You will design deployment pipelines, observability, and engineering tooling that enable rapid delivery of both AI-powered and traditional cloud-native applications.

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.

Work with Python, PyTorch (or JAX/TensorFlow), RL fine-tuning frameworks like TRL or verl, and distributed multi-GPU training. The Reinforcement Learning Team advances RL, Bayesian optimisation, AI agents, LLMs, and vision-language models, applying them to AI for science, chemistry, physics, and robotics while publishing at top venues.

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 Nvidia GB200 72NVL CX8 and AMD MIxxx architectures, coding in C, C++, C#, Java, JavaScript, or Python to benchmark, profile, and debug GPU clusters. You will help build foundational models powering Microsoft’s personalized AI assistant, Copilot, spanning training and inference infrastructure, model architecture, and data curation.

White & Case★4.0 (120)· London

Works with Python, JavaScript, MCP, agentic AI frameworks, LLMs, and cloud platforms (Azure, AWS) to architect and deploy AI tools. As technical lead of the Applied AI Lab, the role oversees design, development, testing, and deployment of AI solutions to support legal practice and firm-wide innovation. Manages and develops a multidisciplinary team of legal engineers.

You will work with Python, JavaScript, Model Context Protocol (MCP), agentic AI frameworks, LLMs, and cloud platforms (Azure, AWS). As technical

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.

Work with AWS, Kubernetes, Slurm, PyTorch, and distributed training frameworks to build foundation model AI for physical intelligence, enabling robots to learn tasks from a single human demonstration. This hands-on role focuses on GPU compute optimisation, cluster scheduling, and high-performance networking within a small, elite team in London.

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.

Staff AI Engineer will use Python, Azure, LangChain, Semantic Kernel, LLMs, and RAG to build production-ready patterns for agentic AI, prompt engineering, and responsible AI. This cross-cutting role connects AI ambition to delivery across all Tech domains at Sainsbury's, creating reusable accelerators and standardising AI engineering division-wide.

You will work with LLMs, generative AI, Python, JavaScript, React, HTML, CSS, Microsoft Azure, and DevOps tools (CI/CD, Git). You will design, build, and deploy AI applications that enhance productivity, automate workflows, and support business decision-making across a growing technology function.

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.

Flo Health★4.8 (26)· London

Lead a team building shared AI infrastructure powering Flo’s chatbot, cycle predictions, and health insights. Work with Databricks, OpenAI, Anthropic, and AWS, managing MLOps, model serving, and LLM stacks in production.

Trainline★3.9 (17)· London

You'll work with Python, Pandas, NumPy, Scikit-learn, Spark, Docker, Terraform, MLflow, CI/CD, and LLMs (fine-tuning, RAG, agents). The team builds production ML and AI solutions powering Trainline's search, recommendations, pricing, routing, personalization, digital marketing, and customer support across rail travel.

Works with Azure cloud, LLMs, vector search, MLOps, CI/CD, data pipelines, and machine learning techniques like NLP. Leads design and delivery of AI/ML solutions across multiple squads to support the bank’s AI strategy.

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.

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.

Monzo★3.5 (108)· London

You'll work with Go, Python, Kubernetes, AWS, GCP, Terraform and Envoy Proxy to build backend services, libraries and tooling for Monzo's ML Platform team. This team helps internal engineers train, evaluate, deploy and serve machine learning models safely and reliably, supporting critical systems like fraud detection and credit decisions across the bank. You'll focus on platform engineering, developer experience and operating distributed systems at scale.

You'll architect and deploy AI systems generating ad creatives using LLMs, vision and diffusion models, code generation, and multimodal asset generation, working with Python, JavaScript/TypeScript, and HTML. The Creative GenAI team at Liftoff—an AI-powered performance marketing platform serving 6,600+ mobile businesses—tackles end-to-end creative production including interactive playables, from prototyping through production pipelines. You'll report to the Senior Director of Creative GenAI, mentor engineers, and drive innovation in generative AI for ad tech.

Nebius★0.0· London

You'll work with Kubernetes, Prometheus, Grafana, Terraform, Python, and Bash to own the reliability, performance, and observability of Token Factory's inference platform—which deploys foundation models (text, vision, audio, multimodal) at massive scale across Nebius Cloud's tens of thousands of GPUs. Your focus spans telemetry pipelines, autoscaler tuning, infrastructure-as-code, request routing, incident response, and cost optimization. Experience with GPU workloads (vLLM, Triton, Ray), MLOps, or model-hosting platforms is valued.

Thomson Reuters★3.9 (4.3k)· London

You'll work with PyTorch, JAX, HuggingFace Transformers, vLLM, LLM APIs, Ray, Spark, and experiment tracking tools like Weights & Biases and MLflow on Thomson Reuters' Foundational Research division, which develops advanced algorithms and training techniques for Large Language Models including LLM training, post-training techniques for reasoning and workflows, data-centric ML, and evaluation. You'll design and implement scalable systems for training, fine-tuning, and evaluating LLMs while translating cutting-edge research into production implementations.

LSEG★3.7 (402)· London

You'll lead a team of quantitative analytics and AI engineers building LLM-powered analytics solutions using Python, cloud platforms (Azure preferred), Databricks, Snowflake, and orchestration frameworks like LangChain and AutoGen. The role focuses on developing next-generation AI-driven analytics and agent-based systems for LSEG's financial markets clients through its Microsoft partnership, with responsibilities spanning LLM engineering, cloud-native architecture, MLOps, and team leadership. You'll manage engineers while architecting scalable data pipelines, RAG systems, and API-first SaaS/PaaS products for risk modeling and intelligent reporting.