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 Python, LLMs, RAG pipelines, vector databases, Hugging Face Transformers, LangChain, PyTorch, and Docker to build production AI systems. Design, develop, and deploy AI-powered solutions such as conversational AI, document intelligence, and backend services for the Global Analytics team.

Develop backend services using Node.js, Python, Java, C#, PHP, and Ruby on Rails, with databases including MySQL,

You will build and evolve customer-facing interfaces for AI Virtual Agents using React, TypeScript, Next.js and Vite, and refactor the frontend into a scalable platform with a shared component library and design system. Unitary’s factory builds custom operations agents that complete complex workflows end-to-end in customer tools.

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.

Java (JDK 11+), multithreading, SQL/NoSQL databases (Oracle, MySQL, PostgreSQL, MongoDB, Cassandra), message queuing (Kafka, Tibco, Solace), Linux, JVM, and TDD. This tech lead role builds high-performance FX risk calculation systems for Citi’s Markets technology team, which supports global trading and risk management.

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.

Koinly★3.0 (1)· London

Work with React 19, TypeScript, TanStack (Router, Query, Table), Radix UI, Mantine, Tailwind CSS v4, Vite, Vitest, Storybook, Highcharts, Sentry, Bun, and RabbitMQ on a data platform that reconciles crypto transactions and tax obligations for Koinly’s web application, with a React Native mobile app joining scope later.

You'll build scalable data infrastructure for AI applications using Python, SQL, Spark, dbt, LangChain, and cloud platforms (AWS, Azure, GCP), working with data pipelines, embeddings, vector search, and LLMOps tools like Terraform and LangSmith. QuantumBlack, McKinsey's AI division, develops next-generation AI systems and enterprise solutions for clients across industries. You'll collaborate with Data Scientists and ML Engineers in cross-functional Agile teams based in London, supporting the firm's AI adoption and complex problem-solving at scale.

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.

Lead engineers use Java, C#/.NET, Python, TypeScript, JavaScript, React, Go, Ruby, Scala, R, and SQL; Git, MacOS/Linux, and CI/CD; and AI-assistive tools. They lead multi-client software consultancy engagements, building and delivering production agentic systems and ML-powered features. The team is typically one to two clients per year.

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.

SQL, MySQL, PostgreSQL, Doris Event, QuickSight, and possibly Amplitude, Mixpanel, GA4, Airbridge, Adjust, Airflow, dbt, Git or Python. You will own analytics schema, data models, and BI dashboards for ZYMIX, a Gen Z social super-app launching in the UK, bridging product analytics with data building.

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.

You will work with JavaScript, PHP, HTML, CSS, Laravel, Bootstrap, APIs/JSON/XML, MySQL, and optionally React. As part of a fullstack team, you will design, build, and maintain frontend and backend systems for a fine bridal jewellery manufacturer’s online platform, migrating legacy systems to Laravel.

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.

Cato Networks seeks a Senior Full Stack Engineer for their secured access team to design and build web security solutions and internal infrastructure platforms using Java, Go, Spring Boot, GraphQL, PostgreSQL, MySQL, MongoDB, and Redis. The role involves end-to-end development from large-scale data processing to web interfaces, working on enterprise SaaS microservices at scale across security products and infrastructure. Requires 6+ years backend development experience, SaaS microservices expertise, and familiarity with relational/non-relational databases in CI/CD environments.

Infosys★3.8 (17k)· London

You will work with Java, Spring Boot, Hibernate, JPA, React/Angular/Vue.js, HTML5, CSS3, JavaScript, RESTful APIs, SQL/NoSQL databases, Git, and CI/CD tools on cloud platforms (AWS, Azure, GCP). As a Senior Consultant at Infosys, a global digital services and consulting firm, you'll contribute across the consulting lifecycle—defining problems, proposing solutions, and guiding development, configuration, and deployment while mentoring teams and shaping client-focused solutions. Docker and Kubernetes experience is a plus.