Wise★3.5 (42)· London

Lead a growing Solutions Engineering team in EMEA, providing technical consulting and product guidance to top-tier banks integrating Wise’s international finance products via REST API. Work with RESTful design, OpenAPI, OAuth2, and microservice architecture to architect integrations and influence the product roadmap.

A Senior AI Engineer at Stakemate will use agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG, Python, cloud services (Azure/GCP/AWS), and SQL to move AI from experiments to production. They will shape the platform and architecture for a live betting product at a fast-growing social sports betting startup.

You will work with agent frameworks (LangGraph, LlamaIndex, Semantic Kernel, ADK), RAG pipelines, vector stores, Python, SQL, and a major cloud (Azure AI Foundry, GCP, or AWS). You will take AI agents from proof-of-concept to production within Stakemate’s live sports betting product, setting the governance and standards for the company’s AI estate. Reporting to the CTO, you will shape the platform and architecture as the company scales.

Design, build and deploy production Generative AI applications, LLM-powered solutions and agentic frameworks using Python, LangChain, LangGraph, and OpenShift. You will automate enterprise workflows with intelligent agents, working with PostgreSQL and pgvector as part of Citi’s COO-Technology team building scalable AI for global operations. This is an Individual Contributor Staff Engineer role.

Google★4.3 (6.2k)· London

Google Cloud AI offerings (Vertex AI, Gemini), modern multi-agent systems (LangGraph, CrewAI). This role drives Gemini Enterprise adoption by industrializing AI excellence, moving licenses to activated, and ensuring production-grade deployment of AI agents and workflows. It leads the GE Accelerator efforts.

EXL Service★3.7 (2k)· London

Design AI architectures on Azure using .NET, React, LLMs, RAG, OCR, and agentic frameworks (LangGraph, AutoGen, CrewAI) to build production-grade GenAI platforms. The role focuses on processing complex insurance documents for underwriting, claims, and reinsurance use cases. You will lead and mentor a team of .NET, React, and GenAI developers.

Pipedrive★4.2 (5)· London

Lead a growing team of Applied Scientists and AI/ML Engineers at Pipedrive, a cloud-based CRM platform serving over 100,000 companies. You'll own the technical strategy for AI/ML solutions working with structured CRM data and unstructured content, designing autonomous agentic workflows using LangGraph, RAG architectures, vector databases, and LLMOps infrastructure. The role requires 8+ years of applied ML/AI experience in production environments, deep expertise in modern AI engineering, cloud infrastructure (AWS/GCP), and distributed systems, with proven ability to lead and scale technical teams.

Design AI architectures on Azure using .NET, React, LLMs, Azure OpenAI, RAG, Agentic AI (LangGraph, AutoGen, CrewAI), OCR, microservices, and Azure AI Search. Build scalable GenAI platforms for intelligent automation in insurance functions like underwriting, claims, and reinsurance. Lead and mentor .NET, React, and GenAI developers.

You will work with React/Next.js/TypeScript and Python on an agentic AI platform that ingests sustainability data, runs scenarios and recommends actions. The company is building a workflow and decision-making layer for sustainability, using AI agents and a knowledge context graph.

Work with Azure OpenAI, AI Foundry, Databricks Mosaic AI, MLflow, Genie, AgentBricks, LangChain, LangGraph, AutoGen, Delta Lake, DLT, Unity Catalog, Python and SQL. You will design, build and deploy GenAI, RAG and Agentic AI solutions from prototype to production as part of a major AI and data transformation programme across a global energy organisation’s trading business.

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

This role uses Google Cloud Platform (GCP), Vertex AI, Gemini models, LangGraph, CrewAI, and ADK to build agentic workflows, MCP servers, and RAG-like architectures. You embed with strategic customers to code, debug, and ship production-grade GenAI solutions, addressing integration, data readiness, and state-management blockers. You also build evaluation pipelines and observability frameworks while co-building with customer engineering teams.

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.

You'll work with Python, TypeScript, C#, Azure, React/Angular, Power BI, Copilot Studio, Claude Cowork, LangChain, LangGraph, and AI orchestration frameworks. You'll design, build, and scale AI agents, automation workflows, integrations, APIs, and RAG pipelines for a professional services organisation investing in AI and cloud technology.

Build production-grade generative AI systems using Python, LlamaIndex, LangChain, LangGraph for RAG pipelines and agentic workflows at an award-winning B2B consultancy. Emphasizes evaluation for correctness and reliability, with hands-on technical leadership and mentoring.

Develop full-stack applications using React, Python, and agentic AI tools including LangChain, LangGraph, and DeepAgents, with experience coding agents like Claude Code. The role supports products in the Private Equity domain.

Wise★3.5 (42)· London

Build backend

Capgemini★3.7 (11k)· London

You will work with Python, LLMs (GPT, Claude, Gemini, Llama, Mistral), RAG pipelines, vector databases (Pinecone, FAISS, ChromaDB, Weaviate, Milvus), and frameworks like LangChain, LangGraph, Semantic Kernel, CrewAI, or AutoGen. You will design, develop, and deploy generative AI applications for enterprise use cases at Capgemini, an AI-powered global business and technology transformation partner.

Equinix★3.7 (391)· London

You will design and ship LLM-powered agents and the platform they run on using Python or TypeScript, APIs, microservices, event-driven architecture, Git, CI/CD, and cloud platforms, with tools like MCP and A2A. The Equinix Incubation team builds agentic systems that automate the software delivery lifecycle end to end—from intake and business case through code, test, release, and value tracking—with humans directing every gate.

Samsung Electronics★3.9 (10k)· London

You'll work with Python, RAG, vector databases, AWS Bedrock, Claude, and agentic frameworks (LangGraph, CrewAI) to build GenAI automation for Sales, Marketing, Finance, HR, Legal, and Operations. You'll architect agentic workflows and multi-agent orchestration, owning the end-to-end AI lifecycle on a small, senior, high-trust team.

ByteDance★3.8 (238)· London

Embedded in customer environments, you will rapidly develop and debug AI applications using Prompt Engineering, Fine-Tuning, RAG, and Agent frameworks like LangGraph or CrewAI, integrating with cloud service APIs/SDKs. You will build production-grade Agent systems, evaluation pipelines, and observability frameworks. This role is with ByteDance, the company behind products such as TikTok.

Build and deploy GenAI automation tools on AWS Bedrock, Claude, and AnythingLLM using Python, RAG, and vector databases. You will design agentic workflows and multi-agent patterns to automate cross-department business processes for Sales, Marketing, Finance, HR, Legal, and Operations at Samsung Ads. This is a senior hands-on role on a small, high-trust team.

ByteDance★3.8 (238)· London

Embedded in customer environments, this role rapidly develops and debugs AI applications (Prompt Engineering, RAG, Agent systems) using cloud architecture, Vibe Coding, and frameworks like LangGraph or CrewAI. The BytePlus team builds production-grade Agent systems integrated with customers’ APIs and data systems.

You will work with Azure (AI Foundry, AI Search, Cosmos DB, API Management, observability), Langfuse, Datadog, LiteLLM, MCP gateways, contemporary AI models, agent harnesses (Claude Code, Codex, GitHub Copilot), OpenTelemetry, LangChain, LangGraph, and Azure document-processing services. The team builds and experiments with AI agents and retrieval-augmented generation (RAG) systems at LSEG, a global financial markets infrastructure and data company. The role is at the Manager career stage.

Develop and debug AI applications in production, using Vibe Coding, Prompt Engineering, RAG, and Agent frameworks like LangGraph or CrewAI. You will build prototypes and production-grade Agent systems within customer environments, integrating with their APIs and data systems. You’ll design cloud architectures and create observability frameworks for accuracy and latency.