Top AI Jobs in London

Partner with startup founders and engineering teams to architect, evaluate, deploy, and scale LLM applications on the Claude Developer Platform. Serve as a technical advisor throughout adoption, lead technical evaluations, develop AI performance frameworks, communicate customer insights to Product and Engineering, and represent Anthropic at customer sites and industry events.

Own Gridsight’s enterprise sales expansion across GB and Ireland, managing the full sales cycle from account prioritization and consultative discovery through tenders, procurement, and contract closure. Build pipeline and forecasting processes from scratch, develop utility partner and channel relationships, and collaborate with technical, delivery, and regional leadership teams. The role targets regulated electricity distribution and system operators with complex, multi-year B2B software sales.

Build and deploy scalable AI applications, intelligent agents, and AI-powered features in production. Collaborate with research, data science, and product teams; evaluate emerging AI technologies; and promote responsible AI through bias detection, explainability, and safety alignment. The role requires production machine learning experience, strong Python and AI framework skills, cloud and MLOps experience, and expertise in deep learning, NLP, and large language models.

Leads an engineering team developing secure developer tools, hardened GitHub Actions, AI agent capabilities, and microVM-based products. Owns product roadmaps, hiring, team growth, technical design, code reviews, delivery, quality, reliability, and customer feedback loops. Partners with Product to prioritize and ship iteratively in an autonomous, ambiguous environment while remaining technically hands-on.

Owns Infinigate Cloud’s AI Productivity portfolio, driving revenue, profitability, partner activation, pipeline, and adoption of Microsoft 365, Copilot, and Azure AI solutions. Develops go-to-market campaigns, recruits and grows strategic partners, manages Microsoft and partner relationships, and provides UK&I subject-matter expertise. Supports partner enablement, events, webinars, process improvements, and internal coaching while maintaining strong customer satisfaction and commercial performance.

Build secure, scalable generative AI services, applications, APIs, microservices, and agentic workflows for enterprise customers. Own system architecture from proposal through deployment, develop React and TypeScript interfaces, and partner with DevOps on continuous deployment, monitoring, logging, performance, and security. Collaborate with product, data science, and engineering teams while mentoring peers and delivering resilient production software.

Lead development of multimodal AI products for G2’s software marketplace. Build agent-driven user journeys, multimodal image and audio features, scalable full-stack systems, and production-quality evaluation workflows. Partner with product owners on requirements, scope, prioritization, and rapid MVP delivery. Manage, mentor, and provide technical leadership to engineers while advancing agent-first development practices.

Analyzes current and future business processes, gathers and documents requirements, coordinates stakeholders, supports solution design, develops and reviews test cases, and facilitates user acceptance testing. The role also evaluates AI model accuracy and performance, contributes to business transformation initiatives, and supports ongoing solution implementation and user needs across multiple projects.

Build and deploy production-grade agentic AI applications, generative AI features, RAG pipelines, and LLM integrations for customer engagements. Develop Python and FastAPI services, model data with relational and graph databases, implement governance guardrails, and instrument systems for observability. Collaborate with platform engineering on deployment and MLOps/LLMOps, modernize legacy workflows, troubleshoot reliability issues, and contribute reusable AI patterns and best practices.

Write addictive 1–3 minute AI-generated micro-drama episodes and complete series arcs for women aged 35–55. Create strong hooks, emotional stakes, cinematic scenes, and cliffhangers using Claude, GPT, and other AI tools. Test formats, analyze performance data, identify plot holes and continuity issues, and provide feedback on final episodes. The role is fully remote and requires native-level English, visual storytelling ability, and strong attention to detail.

Own the backend and agent systems powering LLM products, including multi-turn conversations, tool calling, RAG, state management, evaluations, monitoring, and production reliability. Diagnose failures across models, knowledge systems, tools, and infrastructure; establish regression testing and quality measurement; and guide product and technical decisions. The role requires shipping and improving LLM features at scale, strong backend engineering, disciplined evaluation practices, and preferably Web3 experience.

Develop and evaluate LLM applications, agentic systems, and retrieval pipelines for maritime data. Partner with Product Managers to prototype AI solutions, define evaluation criteria, design architectures, and transition successful work into production. Build embedding and retrieval pipelines, evaluation suites, guardrails, observability, and responsible AI practices on Azure and Databricks. Communicate findings, contribute to shared tooling, and guide adoption of effective AI technologies.

The role involves leading new product development, identifying market opportunities, and driving commercial strategies and partnerships to launch products in the payments sector.

Design, build, and deploy scalable AI architectures, pipelines, LLM integrations, RAG systems, and multi-agent workflows. Operationalize generative AI and NLP solutions in production, collaborate with data engineers on infrastructure and vector databases, and champion AI-assisted coding practices. Provide technical consulting to clients, mentor teams, and advise on AI product development, modern data stacks, synthetic data, and explainable AI.

Own the quality strategy and end-to-end testing pipeline for an AI-generated product handling real-money transactions. Build automated UI, browser, mobile, pre-merge, nightly, release, and production testing gates; integrate testing with CI/CD; evaluate external tools; and improve reliability of critical financial flows. The role partners with engineering and DevOps, uses AI coding agents daily, and drives quality initiatives as an autonomous individual contributor.

Research and develop SLAM, VIO, 3D spatial perception, and camera pose estimation algorithms for resource-constrained edge devices. Translate research into real-time, low-latency neural and spatial pipelines running on mobile NPUs, DSPs, and GPUs. Build on-device capabilities for augmented reality, enterprise vision, barcode recognition, OCR, and multimodal edge AI while collaborating with hardware, software, and product engineering teams.

Leads the technical direction and delivery of enterprise AI programs, designing agentic systems, multi-agent workflows, RAG pipelines, and generative AI applications. Builds production Python services, integrates databases and LLM tooling, establishes AI governance and observability, and partners with platform engineering on deployment. Translates enterprise needs into AI roadmaps, provides architectural oversight, mentors engineers, codifies reusable patterns, and communicates outcomes to senior stakeholders.

The Head of Research and Development for AI Safety will lead a research team focused on AI safety, drive the research agenda, manage publications, and influence AI safety strategies with industry impact.

Leads OpenAI’s Applied AI Architect team across Europe, developing technical strategy and operating models for strategic enterprise customers. Oversees customer journeys from discovery through production adoption, coaches senior architects, manages resources, advises executives, and coordinates Sales, Product, Engineering, Research, Security, Legal, Privacy, and deployment specialists. Ensures secure, scalable architectures, responsible AI adoption, measurable customer outcomes, portfolio health, and expansion opportunities.

Leads Gartner’s AI Infrastructure investment research practice, producing market insights, predictions, strategic investment frameworks, and client advice across semiconductors, AI hardware, data centres, and compute. The role requires translating complex technical architectures into commercial and investment insights, presenting to executives and institutional investors, supporting sales and conferences, mentoring analysts, and shaping research agendas.

Lead design and delivery of production-grade AI/ML solutions for Market Operations. Manage a team of data scientists and partner with engineering and business stakeholders to build, deploy, monitor, and govern models, establish best practices, and drive measurable operational impact.

Lead AI-driven data and analytics programmes in financial services, mentoring teams and ensuring delivery of measurable outcomes.

Turn utility network data, including AMI, topology, and asset telemetry, into reliable analysis and visualizations. Own customer delivery across pre-sales, pilots, and deployments; lead working sessions; present findings; translate technical concepts; adapt the platform to UK and European grid operators; and build the regional delivery playbook. The role requires strong hands-on data skills, commercial judgment, customer communication, rapid learning, AI-enabled workflows, and comfort operating as an early hire.

Gridsight invites exceptional candidates in the United Kingdom to submit an expression of interest for future opportunities. The company develops SaaS solutions using data, machine learning, and AI to modernize electricity-grid operations, support renewable connections, and orchestrate distributed energy resources. Applicants should explain their achievements, impact, motivation, learning ability, and alignment with Gridsight’s low-ego, high-impact culture.

Build modular, config-driven AI video generation pipelines for mobile gaming advertisements. Integrate fal.ai models and APIs, orchestrate reliable asynchronous jobs, manage retries and resumable execution, track costs, and use FFmpeg for video assembly, subtitles, overlays, audio mixing, and format conversion. Document workflows so marketing teams can operate them without coding, while collaborating with creative specialists and demonstrating a working pipeline.