Top AI Jobs in London

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.

Drive AI adoption across an M&S business unit by identifying and embedding use cases into workflows, tracking value and adoption, coaching colleagues, building champion networks, communicating success stories, and feeding business needs into the AI Accelerator. Ensure adoption aligns with responsible AI, fair usage, and data governance frameworks.

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.

Define and standardise end-to-end LLM architectures and reusable AI solution patterns. Design data pipelines, RAG, prompt orchestration and CI/CD for safe production deployment. Set monitoring, evaluation and prompt-testing standards. Lead engineering teams, address product/data/security/legal constraints, and collaborate with stakeholders to deliver AI solutions for regulatory priorities.

Design and run empirical experiments to find how LLM agents fail in realistic settings; build automated audit agents, fine-tune and run models, perform white-box and black-box investigations, produce evals and publish findings that feed into product guardrails.

Design, develop, and deploy intelligent AI agents, optimize large language models, enable collaboration in customer interactions, and maintain backend systems.

Design, build, and maintain scalable, secure full-stack applications using Java and Angular. Lead integration and deployment of agentic AI, implement microservices and event-driven architectures, collaborate with data scientists, and promote CI/CD, testing, security, and best practices. Mentor developers and support the full software lifecycle in a hybrid enterprise environment.

Senior consulting leader who owns the strategic value narrative and client relationships across data platforms, AI and end-to-end software engagements. Leads discovery, executive workshops, alignment, change management and adoption, supervises delivery leads, supports pre-sales, and grows client engagements through solution shaping and go-to-market propositions.

Partner with sales to qualify opportunities, gather requirements, craft D365 Business Central solution demos and proposals, produce estimates, respond to RFIs/RFPs, support go-to-market content, and build Microsoft ecosystem relationships.

Technical presales role focused on designing, demonstrating, and positioning Copilot Studio AI solutions. Partner with sales and Microsoft teams to qualify opportunities, lead technical discovery, build demos/POCs, advise on orchestration, integrations, security and governance, and help develop repeatable AI offerings and enablement materials.