Top AI Jobs in London

Lead developer engagement for firmwide developer tools to drive safe, practical adoption of AI coding tools. Run demos, workshops, and enablement; create guidance, examples, and playbooks; gather feedback; partner with platform, risk, and engineering leaders to scale adoption across a regulated enterprise.

Support customer-facing AI initiatives by helping discover use cases, build demos and prototypes, configure and test conversational AI experiences, assist integrations with APIs and data sources, participate in workshops and presentations, and document outcomes while learning LLMs, RAG, and prompt design.

The Senior Research Scientist will conduct high-impact AI safety research, lead evaluations and red-teaming projects, and support academic publication efforts in applied AI safety.

As the Technical Director of AI Safety, you'll lead AI safety initiatives, oversee R&D, mentor teams, and drive innovations, representing Faculty in global AI safety discussions.

As an AI Consultant, you'll analyze data, develop AI models, guide junior analysts, and communicate results, focusing on innovative solutions and predictive modeling.

As an AI Deployment Strategist, you'll design and deploy AI-powered planning solutions, interact with clients, and bridge between technical and product teams to drive AI adoption.

Develop and refine NLP projects by improving LLM models, implementing production models, and conducting performance experiments.

This role invites interested candidates to express their interest for future opportunities, emphasizing exceptional talent and a collaborative team environment dedicated to AI advancements.

Own the end-to-end product lifecycle for Sustainable Investment (SI) data platforms: define roadmap; onboard and operationalize new data sources; lead migration from legacy systems to cloud/lakehouse/warehouse platforms; partner with engineering, operations, and commercial teams; and drive data quality, coverage, timeliness, and regulatory/client compliance.

Join the Data Science team to innovate solutions for data problems, develop forecasting models, and enhance quant strategies using machine learning.

This position invites individuals to express interest in future roles at Unlikely AI, focusing on innovative AI technology development and collaboration.

Design and lead enterprise GenAI, conversational AI, and agentic AI architectures for Anaplan’s planning platform. Define architecture patterns, APIs, data models, prompt engineering frameworks, observability, evaluation, guardrails, and scalable production systems. Collaborate with product, engineering, and data science teams; evaluate AI technologies; lead architecture reviews; and mentor engineers delivering secure, reliable AI solutions for forecasting, scenario planning, and financial modeling.

Own the discovery, definition, delivery, adoption, and iteration of AI-powered products that improve business processes. Responsibilities include mapping workflows, identifying AI opportunities, creating roadmaps and specifications, partnering with engineering and applied AI/ML teams, defining evaluation criteria, designing human-in-the-loop adoption workflows, measuring outcomes, and communicating with frontline and executive stakeholders.

Design, automate, secure, and operate AWS and Azure cloud infrastructure supporting AI and generative AI platforms. Build Terraform-based infrastructure, manage networking, identity, containers, Kubernetes, monitoring, governance, and cost controls. Support production operations, incident response, troubleshooting, documentation, and compliance in partnership with AI, Data, Security, and Application teams.

Lead the design and delivery of scalable, secure enterprise software using Go, distributed systems, Domain-Driven Design, event-driven architecture, and cloud-native technologies. Build production AI-native applications incorporating LLMs, RAG, tool calling, and agentic workflows. Partner with Product and Design, solve complex customer problems, mentor engineers, lead technical initiatives, and promote engineering excellence, observability, testing, security, and operational readiness.

Lead technical direction for an AI platform connecting workloads to multiple LLM providers. Build API gateway and routing infrastructure, agent orchestration, capability lifecycle tooling, access controls, API key management, caching, cost and latency optimization, adoption analytics, and trust, safety, and governance controls. Define API standards and promotion workflows while supporting auditable, scalable AI services across client engagements.

Own the revenue operations systems, data, analytics, and AI infrastructure across multiple healthcare verticals. Manage HubSpot, BigQuery, and Metabase; build dashboards, automations, integrations, AI tools, and commercial workflows; identify risks and insights; and improve sales, marketing, finance, and leadership effectiveness. This first RevOps hire will partner closely with commercial and executive teams to build scalable systems and processes.

Build and maintain on-device LLM software that transforms live neuromonitoring signals into actionable clinical insights. Responsibilities include AI integration, model evaluation, prompting, guardrails, inference optimization, medical device software development, cybersecurity and regulatory compliance, and fleet reliability. The role requires close collaboration with hardware, product, and clinical teams while ensuring safe, reliable performance on constrained hardware.

Manage a cross-functional engineering team building GitLab Duo Chat's AI-powered features. Define requirements with product and UX, contribute to architecture for scalable agentic AI, drive delivery and roadmap execution, improve testing, observability, performance, and coach engineers to foster an inclusive, high-performing team.

Enable firmwide adoption of generative AI by embedding with teams, providing user support, delivering workshops, creating guidance and communications, evaluating AI tools, and gathering feedback. The role translates technical capabilities into practical business workflows, supports senior stakeholders, tracks adoption barriers, and contributes to tool rollout and optimization. International travel is required as needed for training and team support.

Build and deploy AI solutions that transform Sales, Marketing, Finance, HR, Legal, Procurement, and Customer Success workflows. Partner with business leaders to identify opportunities, manage end-to-end delivery, measure adoption and business impact, and provide AI enablement. Develop applications using LLMs, RAG, agents, MCP, evaluation frameworks, and guardrails while leveraging shared infrastructure and driving organizational AI fluency.

Own the technical side of enterprise sales for an agentic AI platform. Partner with sales teams and founders to understand customer needs, build tailored demos and proofs of value, assess architecture and integration feasibility, and address security and technical concerns. Engage stakeholders from HR and IT through executive leadership, create repeatable presales enablement systems, provide product feedback, and help shape the platform’s technical positioning. The role requires hands-on AI and integration expertise, commercial judgment, and travel across the US and Europe.

Leads AI strategy and innovation across Finastra’s Universal Banking portfolio. Identifies and prioritizes AI opportunities, translates emerging technologies into product initiatives, validates use cases with banking customers, and drives solutions from ideation through productization and adoption. Partners with Product, Engineering, Sales, Partners, Legal, Compliance, Security, and Architecture teams to deliver measurable commercial and customer value. Establishes responsible AI governance, risk controls, success metrics, investment recommendations, and executive visibility.

Drive complex, end-to-end AI and business transformation sales for strategic healthcare customers. Own account planning, pipeline creation, opportunity management, negotiation, forecasting, and deal execution. Engage senior business and IT stakeholders, develop business cases using value and TCO analysis, guide evaluations, coordinate internal and partner teams, and sell enterprise applications, CRM, ERP, automation, and AI solutions.

Designs and delivers enterprise AI solutions using Claude. Acts as a pre-sales technical advisor, translating customer needs into scalable architectures, guiding evaluations and deployments, presenting to technical and executive audiences, and coordinating with Sales, Product, and Engineering. The role requires customer-facing architecture experience, enterprise integration expertise, Python familiarity, LLM knowledge, German and English fluency, and occasional customer travel.