Top AI Jobs in London

Create cinematic films and motion using generative video tools to visualise unbuilt luxury residences and destinations. Collaborate with strategists, designers, editors and producers to develop visual worlds, translate cinematographic craft into prompts and workflows, choose appropriate AI models/tools, and deliver high-quality campaign films.

As an AI Engineer, you will build AI agents for preventive health, focusing on reasoning, clinical workflows, and ensuring reliable production systems.

Own the full enterprise GTM lifecycle: prospecting, discovery, demos, pilots, negotiations, closing, and expansion. Map creative workflows, run product demos and pilots with success metrics, manage complex multi-stakeholder deals, build repeatable GTM processes, and feed customer insights back to Product and Leadership to influence roadmap and positioning.

The Machine Learning Engineer will develop AI systems to enhance insurance claims workflows, deploy scalable ML solutions, and collaborate with insurance specialists.

The AI Engineer will focus on the lifecycle of production-grade AI, managing model training, fine-tuning, inference optimization, and production engineering, while collaborating with stakeholders to implement business requirements.

Lead AND Digital's Data & AI practice: define go-to-market strategy, advise C‑suite, design value-driven Data & AI solutions, grow revenue and partnerships, mentor teams, and ensure delivery excellence.

Entry-level role for recent graduates to research and support Data & AI innovation. Responsibilities include trend research, using GenAI tools (e.g., Claude), developing client-facing presentations, collaborating with senior experts, and contributing to new Data and AI offerings.

Lead technical pre-sales for AI and data opportunities across the UK public sector. Shape solution strategies, conduct client workshops, lead bids and procurements, advise on responsible AI adoption, and develop differentiated AI propositions. Provide expertise in generative and agentic AI, machine learning, LLM solutions, data foundations, governance, evaluation, and production adoption. Build senior stakeholder relationships, support demonstrations and proofs of concept, mentor colleagues, and ensure proposed solutions are practical, secure, scalable, ethical, and deliverable.

The AI Research Engineer will develop AI models to enhance product autonomy, analyze extensive data, and deliver impactful solutions, driving innovative product features.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Lead global R&D to define technical strategy and roadmaps, prioritize AI-driven modernization, manage engineering and test teams, oversee AI/ML model validation in regulated clinical environments, own R&D budgeting and vendor partnerships, ensure regulatory compliance, and drive operational excellence and ethical AI adoption to improve clinical trial outcomes.

Design and own end-to-end agentic AI workflows on the Microsoft AI stack, focusing on agent orchestration, human-in-the-loop controls, cost optimization, secure enterprise integrations, governance, and phased multi-country deployments. Define reference architectures, optimize model routing and token budgets, and ensure compliance and auditability while evaluating emerging agent frameworks.

Deliver an AI-enabled DevOps and automation capability: design scalable CI/CD patterns, integrate Azure AI Foundry and AI services into pipelines, implement IaC and operational tooling, improve SDLC with AI, and provide documentation and structured knowledge transfer to TMHCC engineering teams.

Provide legal counsel on AI and data protection across customer, partner and supplier contracts; lead EU AI Act readiness and ISO 42001 alignment; advise on IP, data transfers, DSRs, audits, incidents and regulator engagement; draft playbooks, run trainings, and support multilingual contracting (French/Spanish) in a fast-growing AI/SaaS environment.

Lead design and delivery of AI-enabled transformation across global accounting: consolidation, R2R, tax, and revenue recognition. Redesign processes to be AI-first, embed AI agents and automation, ensure controls and audit compliance, strengthen validation and monitoring, build team capability, drive adoption through training and standardization, and align with broader finance transformation programs.

Lead EMEA go-to-market for Physical AI by sourcing executive-level pipeline, accelerating top accounts, building EMEA-specific playbooks, enabling regional sales, and converting lighthouse wins into sustained cloud consumption across robotics, autonomy, simulation, and related AI-native industries.

Lead quality engineering across product teams with an automation-first approach: build test frameworks, CI tooling, AI-assisted testing agents, performance benchmarks, reliable E2E suites, reduce flakiness, drive shift-left quality, and close the loop with observability to improve SLOs and reduce incidents.

Lead quality engineering across product teams with an automation-first approach: build test frameworks, AI-assisted testing agents, CI tooling, SLOs, performance benchmarks, reduce flakiness, improve test data and environments, and partner with product and engineering to prevent defects and close the loop on production issues.

Full-stack AI/ML Software Engineer to build HealthTech SaaS microservices, implement and integrate ML solutions, write high-quality code, author documentation, perform code reviews, and act as an SME on services and systems.

The AI Engineer designs, develops, and deploys AI-driven applications for non-data scientists, enhancing decision-making and model accessibility for organizations.

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.

Lead Mark43's AI-enabled engineering initiative by designing and orchestrating multi-agent systems that plan, write, review, test, and deploy software. Write prompts, scaffolding, and tool integrations (VCS, test runners, internal APIs), evaluate agent performance, prototype LLM-based workflows, collaborate cross-functionally, mentor teammates, and contribute to on-call rotations.

Lead the strategic direction of Paid Search and AI advertising across international accounts. Develop cross-channel, full-funnel strategies, embed a testing-and-learning culture, evaluate emerging AI ad formats (including ChatGPT), provide client-facing strategic consulting, lead and mentor the SEA team, and drive pitches, presentations, and operational initiatives for scalable performance.

As an AI/ML Software Engineer, you'll develop systems that transform audio and video data into structured insights, focusing on prompt engineering, agent systems, and model optimization.