Lead the EMEA Solutions Engineering team for Wise Platform, working with REST APIs (RESTful design, OpenAPI, OAuth2) and microservices architecture. The team helps top-tier banks and tech companies integrate Wise’s international finance products via their public API, providing post-sale technical consulting. You will build and mentor a high-performing technical delivery team, defining goals aligned with Wise Platform’s objectives.

Lead TypeScript and Python development, CI/CD, and API-first design to embed AI into production software platforms. You will modernize legacy systems toward service-based architectures and guide integration with AI services like MCP, working across DevOps, platform engineering, and data science teams.

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.

Senior WordPress Developer role: build bespoke WordPress sites and apps using PHP, MySQL, ACF, WooCommerce, Gutenberg, JavaScript (ES6+), SASS/SCSS, Git, Composer, npm, Vite, CI/CD. You’ll also drive AI-assisted development (RAG, MCP, Copilot) and mentor junior 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.

Insulet Corporation★3.1 (189)· London

Lead a globally distributed MuleSoft engineering team owning the AI Enablement Integration portfolio. The role works with MuleSoft Anypoint Platform, AI Gateway, Model Context Protocol (MCP), Agent Fabric, CloudHub 2.0, and Flex Gateway to make enterprise systems and APIs securely available to AI agents and automation platforms.

Sovos★3.3 (105)· London

Design and build Snowflake architecture and dbt model infrastructure for the topline financial data chain (billing, ARR, revenue recognition) at Sovos, a global tax compliance leader. Use advanced SQL, dbt, and optionally Python, Azure/AWS, and MCP to deliver production pipelines that support FP&A, Accounting, and AI consumers through financial close.

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.

Build sub-80ms retrieval and ACL-gated state infrastructure for multi-agent coordination using LangGraph, CrewAI, AutoGen, and custom frameworks. Own the core retrieval, SDK, and API surface end-to-end. This is a founding engineer role working in-person daily with a small team in London.

Design and build the Snowflake schema and dbt model architecture for the financial data pipeline, owning ingestion, transformation, and close-ready outputs for FP&A and Accounting. You will also extend dbt models for OPEX, COGS, and commissions, and integrate CRM/ERP systems like NetSuite or Salesforce. This role supports Sovos’ global tax compliance platform.

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.

Insulet Corporation★3.1 (189)· London

You will lead a globally distributed MuleSoft engineering team, using MuleSoft Anypoint Platform, AI Gateway, MCP, Agent Fabric, API-led connectivity, CloudHub 2.0, and Flex Gateway to build secure, governed integration capabilities for enterprise AI agents, automation, and intelligent workflows. This role owns the AI Enablement Integration portfolio at Insulet, a company pioneering “Liveable Technology” to transform diabetes care.

Lead AI engineers use Python, LangChain, vector stores, and LLMOps tooling to build and operate production generative AI applications like copilots and agentic workflows. They design RAG pipelines, own end-to-end development, and integrate with enterprise data systems and APIs. This player-coach role seeds and grows the AI Engineering function within GCG technology at Capital Group, a global investment firm.

You’ll use Python, LLMs, RAG pipelines, embeddings, vector storage, and cloud-native tools to build production generative AI applications—copilots, assistants, and agentic workflows—that improve Capital Group’s investment process.

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.