Lead a team of Data Scientists and ML Engineers building AI solutions for financial markets using LLMs, Generative AI, Deep Learning, Transformers, Agentic AI, Python, PyTorch, TensorFlow, Hugging Face, LangChain, Semantic Kernel, Azure AI Foundry, AWS AI Services, and MLOps/LLMOps practices.

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.

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.

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 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

You will work with Python, SQL, OpenAI, Azure OpenAI, LangChain, RAG architectures, vector databases (Pinecone, FAISS, Azure AI Search), Azure, AWS, Databricks, and CI/CD tools. As part of Finalto’s AI Innovation team, you will design and deliver AI-powered workflows—such as document processing, bank statement parsing, and news summarisation—that replace manual processes across the business.

AXIS Capital★5.0 (1)· London

You will work with Python, Azure AI services (Azure OpenAI, Azure AI Search), Git, LangChain, Semantic Kernel, and MLOps tools for model versioning, deployment, and monitoring. As deputy to the Head of Data Science & AI Delivery, you lead the day-to-day execution of AI delivery across strategic projects and use cases for AXIS Capital, a specialty insurance and reinsurance provider. You directly manage and contribute hands-on to technical design, code reviews, and solution delivery for a growing team of Data Scientists and AI Engineers.

You'll lead a 4–5 person team building machine learning systems using Python, TensorFlow, PyTorch, JAX, AWS, Docker, and Kubernetes for Super's Playstack platform, which powers sports betting and gaming experiences across Europe and Latin America. The role combines technical contribution, project management, and people leadership, focusing on predictive analytics, personalization, fraud detection, and real-time recommendations that enhance customer engagement in online gambling and sports betting.

Capgemini★3.7 (11k)· London

Architect enterprise-scale generative AI solutions on AWS using Amazon Bedrock, RAG, agentic workflows, and cloud-native services. Define reusable patterns, implement observability, and ensure governance in regulated environments. Hands-on Python, Lambda, SageMaker, OpenSearch, and ECS/EKS.

bp★3.8 (5.2k)· London

You will work with Python, Java, Azure, LLMs, vector DBs, and RAG patterns, using tools like LangChain, Haystack, and Hugging Face. As part of bp's AI organization, you will design and deploy scalable, production-grade AI applications such as conversational bots and AI-powered search for the oil and energy sector.

U.S. Bank★3.5 (12k)· London

Work with CI/CD (GitLab, Jenkins, Harness), Terraform, AWS (ECS/EKS, Lambda, S3, IAM), Docker, Kubernetes, OpenTelemetry, CloudWatch, and Python/Bash. You own the deployment, operations, and reliability of the AI‑SDLC platform as it transitions from local execution to a centralized, hosted enterprise service.

Build and scale data pipelines for large video generation models using AWS S3, DynamoDB, Kubernetes, Python, and PyTorch. You will design annotation workflows across MTurk and Prolific, and train smaller supporting models for data filtering and quality assessment. Cantina Labs is a social AI company developing real-time character models.

At Axon Labs you will own production infrastructure across multi-region cloud and latency-sensitive environments using AWS, Python, C++, Kubernetes, Terraform, CI/CD, PostgreSQL, TimescaleDB, Kafka, Redis, low-latency messaging, Grafana, Prometheus, and Loki. The company is a systematic trading and research lab that builds decision engines running in live markets, with multiple strategies already in production across venues.

You will work with Python, Java, Azure, LLMs, vector DBs, RAG, and frameworks like LangChain, Haystack, Hugging Face, and Crew AI. The AI organization builds and deploys scalable, production-grade AI-powered applications for business value within the oil and energy/HR technology sector.

Build and manage CI/CD pipelines (GitLab/Jenkins/Harness), infrastructure as code (Terraform), and AWS cloud services (ECS/EKS, Lambda, S3) with Docker and Kubernetes for the AI‑SDLC platform. Ensure platform reliability, monitoring (OpenTelemetry, CloudWatch), and operational support, while driving the centralized, hosted enterprise service through automation and security compliance. This role is within the team at Elavon, a U.S. Bank subsidiary building tailored payment solutions.

Autodesk★4.1 (589)· London

You will develop ML pipelines and generative AI features using PyTorch, HuggingFace, and computational geometry with 3D data (meshes, B-Rep models), scaling training with Ray on cloud platforms like AWS or Azure. As part of Autodesk Research, you collaborate with researchers and engineers to integrate ML capabilities into Autodesk’s design and manufacturing products.

bp★3.8 (5.2k)· London

Design, develop and maintain production-grade AI applications using Python, Java, microservices, AWS/Azure/GCP, CI/CD, LLMs, vector DBs, RAG, and tools like LangChain, Haystack, Hugging Face, Weaviate, and LlamaIndex. The team builds scalable AI-powered applications—including conversational bots, AI search, unstructured data processing, and generative BI—to solve high-priority business problems.

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 work with Python, FastAPI, PydanticAI, Langgraph, Langchain, React, AWS or GCP, and containerization/infrastructure-as-code to build production AI systems. The role involves full-stack development—front and back-end—for a FinTech firm's internal AI Centre of Excellence, delivering GenAI solutions including chatbots, assistants, and workflow automation across the enterprise. The team is expanding and expects to triple headcount this year.

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 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.

Productionise GenAI and agentic systems using Python, FastAPI, LangGraph, LangChain, or similar frameworks, along with Docker, GitHub, CI/CD, and AWS. You will design APIs and backend components that integrate LLMs with tools and data sources, bridging the gap between prototypes and production systems for the energy and commodity market intelligence provider Argus Media. As a senior member of the Data Science team, you will mentor colleagues and set engineering standards.