Top AI Engineer Jobs in London

Lead end-to-end deployments of generative AI solutions embedded with business teams: discovery, scoping, architecture, build, and production rollout. Develop LLM-powered applications, write production-grade frontend and backend code, feed field insights into the central AI platform, and drive adoption through measurement and stakeholder communication.

Develop and deploy AI-powered applications, agents, and integrations for HFT. Evaluate models and tooling, build agentic workflows, integrate AI with internal systems, and collaborate with research and trading teams to deliver production-grade AI solutions and best practices.

The AI Engineer will design and build full-stack applications, optimize AI interfaces, and collaborate on integrating AI technologies into enterprise solutions.

Lead the design and development of AI solutions for clients, implementing language models and frameworks, mentoring engineers, and evolving internal AI platforms.

The Principal AI Engineer will define AI architecture, lead teams, develop solutions, and mentor engineers to enhance enterprise AI systems.

As a Senior Product Engineer in AI, you'll build systems for AI products, collaborate with teams, and enhance product experiences while mentoring others.

The AI Engineer will develop the AI infrastructure, build approval workflows, and create intelligent collections agents, ensuring product reliability and customer satisfaction.

As an AI Engineer, you will develop and maintain AI platforms and SDKs, deliver workflows for research, define best practices, and embed in business teams to explore new AI opportunities.

The Full Stack AI Engineer will build and deploy AI-integrated MVPs, develop front-end and back-end systems, optimize ML pipelines, and maintain APIs and cloud infrastructure, focusing on healthcare administration.

The Senior Business Systems Analyst will optimize Salesforce and key business systems, partner with stakeholders to improve processes, and drive automation using AI capabilities for better operational efficiency.

The Senior/Staff Software Engineer, AI will develop AI-powered features, design backend services, and optimize workflows, ensuring integration and user experience. The role requires collaboration across teams to innovate and improve AI applications.

Design and ship production LLM-based internal tools and automation to remove operational friction. Partner with business owners, prototype agentic workflows and RAG pipelines, deploy solutions (automation platforms or Python), maintain observability, run training, and measure impact.

As a Staff Cloud Site Reliability Engineer, you will build and scale AI cloud platform reliability, define operational standards, and lead SRE initiatives.

The role involves building and scaling the reliability of AI cloud platforms, overseeing GPU compute infrastructure, incident response, and operational excellence while collaborating with various teams to enhance system efficiency and resilience.

Lead design and implementation of high-performance agent runtimes, backend services, and self-hosted model/agent infrastructure. Build low-latency execution systems, real-time data pipelines, telemetry loops, CI/CD for zero-downtime deployments, and ensure fleet reliability on AWS/EKS.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

Build and ship native Android features in Kotlin (Jetpack Compose). Integrate backend APIs, improve performance and reliability, collaborate with product and design, use analytics, and implement AI-assisted on-device experiences where valuable.

Build and ship native Android features using Kotlin and Jetpack Compose. Design clean user flows for financial services, integrate backend APIs, improve performance and stability, use analytics and production feedback, and implement AI-assisted on-device experiences where beneficial.

The Applied AI Engineer will develop and deploy AI features, enhance model performance, optimize systems for reliability, and collaborate with teams to address complex problems.

Develop end-to-end AI product features by integrating LLMs and external tools, ensuring system reliability and performance across multiple tasks.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

The Senior .Net Developer will enhance SDG's C#/.NET Core codebase, design high-load services, and optimize MS SQL queries, benefiting from a remote work environment and attractive benefits.

Lead research and engineering for large-scale LLM and multi-modal pre-training: design architectures and tokenizers, curate massive datasets, run distributed training on thousands of GPUs, debug performance bottlenecks, and improve cross-modal alignment and efficiency.

The Applied AI Engineer will design and build LLM-driven automation products, collaborate on AI capabilities, and improve AI performance for wealth management solutions at Nevis.

The software engineer will develop AI tools for sustainability reporting, collaborating on product strategy and ensuring code quality while leveraging LLMs.