Deloitte★3.9 (14k)· London

You will work with large language models, prompt engineering, retrieval-augmented generation, orchestration frameworks, and cloud platforms (Azure, AWS, GCP). As a GenAI Solution Design lead in Deloitte's AI Scaling & Transformation team, you design enterprise-grade GenAI solutions for Security & Justice clients in regulated environments. This Senior Manager role involves overseeing delivery across multiple workstreams and leading mentoring delivery teams.

Lead a hands-on founding engineering role building AI agents for data privacy compliance at Pyxos. Own the control plane, agent architecture, model-abstraction layer, telemetry, evaluation harnesses, and expert knowledge system using LLMs, multi-step agentic workflows, and CI/CD pipelines. You will work with a production system serving enterprise customers, hiring a deliberately small team as the most senior technical leader reporting to the CEO.

You will lead an AI engineering team delivering enterprise AI initiatives including Generative AI, AI Agents and Voice AI, working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering and Python on cloud platforms. This role manages the AI roadmap from concept to production for a major enterprise undergoing AI transformation.

Citi★3.9 (21k)· London

Lead architecture and hands-on development of a greenfield Agentic AI Platform on GCP using Vertex AI, ADK, LangChain, multi-agent architectures, and RAG with Python, Java/Spring Boot, and Kubernetes. The platform empowers Citi’s corporate and investment bankers with autonomous agents to streamline workflows and deepen client relationships.

Accenture★3.9 (29k)· London

You will build production-grade agentic AI systems using LangGraph, CrewAI, AutoGen, OpenAI, Anthropic, Vertex AI, Kubernetes, Docker, Python, and Java. The role designs end-to-end multi-agent systems, RAG pipelines, and LLMOps (LangSmith, Braintrust) while embedding with client engineering teams to deliver enterprise solutions. No team size is stated.

Google★4.3 (6.2k)· London

Lead a squad of AI/ML engineers using Python, AI/GenAI tools, multi-agent workflows, RAG systems, Model Context Protocol, and foundation models. The team codes and deploys bespoke agentic solutions within customer environments for Google Cloud, which delivers enterprise-grade digital transformation. Manage a forward deployed engineering team, providing technical mentorship and setting code standards.

Multiverse★4.0 (5)· London

This role involves Python, TypeScript, React, Next.js, RabbitMQ, and LLMs. The Diagnose & Prescribe (D&P) team owns the learner and employer journey, assessing skill gaps and directing them to suitable apprenticeships or learning paths.

Figma's Developer Tools team is building solutions for frontend and full-stack developers, including Dev Mode, MCP, Code Connect, and emerging AI-powered features. You'll manage a team of product engineers across this initiative—a major focus spearheaded from London—defining strategy and roadmap while providing hands-on technical leadership. The role emphasizes AI product experience, building high-performing teams, and balancing innovation with execution.

Compare The Market★3.3 (20)· London

Lead a machine learning engineering team building production AI systems—real-time inference APIs, batch data products, and LLM-based agentic solutions—using Python, Terraform, GitHub Actions, and ArgoCD. You'll set technical direction, mentor ML engineers, drive delivery, and partner with data, product, and commercial teams to ensure systems scale and improve continuously in Compare the Market's financial services AI platform. The team size is not specified in the listing.

Checkout.com★3.8 (15)· London

You'll lead a data platform team building infrastructure for petabyte-scale analytics and AI systems at Checkout.com, a payments processor handling 10 billion daily transactions. Core technologies include Datadog, SQL, Terraform, Docker, AWS (ECS, Kinesis, SQS, Cloudwatch), GCP BigQuery, with beneficial knowledge of Airflow, Kafka, Flink, dbt, and Kubernetes. You'll manage a team of junior and senior data engineers while ensuring regulatory compliance, delivering quarterly roadmaps, and overseeing AI governance and GenAI production infrastructure.