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.

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.

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.

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.

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.

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.

Work with Python, NumPy, pandas, SQL, dbt, Snowflake/Databricks, and LLMs to build and deploy ML models and agentic systems (function calling, multi-agent orchestration) for Planday’s scheduling and workforce management platform. You’ll ship production features on a small, high-impact team.

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.

FDM Group★2.9 (270)· London

The role involves Python, Java, microservices, CI/CD, cloud (AWS/Azure/GCP), LLMs, vector DBs, RAG, AI agents, and frameworks like LangChain, Haystack, Hugging Face, Weaviate, LlamaIndex, Crew AI, AutoGen. The team builds scalable AI-powered applications (conversational bots, AI search, unstructured data processing, GenBI) for a client in the energy sector.

Unilabs★3.2 (122)· London

AI Native Engineer at Unilabs: Work with LLMs, agentic frameworks (LangChain, LlamaIndex), Python, SQL, REST APIs, cloud infrastructure (AWS/Azure/GCP), Docker, HL7/FHIR, and DICOM to design production-grade AI systems that parse unstructured pathology records into clinical insights. The role builds pipelines and APIs for precision medicine within a European diagnostics company.

Build high-throughput data pipelines, deploy LLMs and ML models, and develop AI tooling working with Python, Spark, Databricks, Airflow, Kafka, KDB, AWS/GCP/Azure, and Kubernetes. The role supports a global investment firm where technology drives performance, building data platforms and AI systems directly used by Portfolio Managers to uncover alpha.

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.

Work with Python, Kubernetes, vLLM, SGLang, and cloud infrastructure (AWS, Azure, GCP) to build POCs, MVPs, and production integrations. As an AI Field Engineer, you embed with customers to deploy and fine-tune LLMs (SFT, DPO, RFT) and architect production inference systems.

Circadia Health's ML Ops Engineer will work with Apache Airflow, AWS (Batch, EC2, S3, IAM, CloudWatch), MLflow, Docker, Python, Git, SQL, Snowflake, and edge devices. You own the ML infrastructure and pipelines for a clinical monitoring platform that identifies early signs of clinical deterioration using predictive models in cloud and edge environments.

You will work with Python, LLMs, GenAI architectures, RAG, embeddings, vector search, AI agents, LangChain, LlamaIndex, LangGraph, Semantic Kernel, AutoGen, Docker, Git, CI/CD, and Azure/AWS/GCP. You build and deploy production-ready GenAI and agentic AI solutions for clients, including RAG architectures and intelligent assistants. You are an individual contributor on multidisciplinary client teams, co-creating solutions from ambiguity to execution.