Top AI Jobs in London

Build and ship agentic LLM systems for Treasury: cash monitoring, funding execution, narrative generation, and discovery-to-deployment pipelines. Create reusable agent infrastructure, governance, evaluation, and partner with engineering to ensure data accuracy while embedding with operators to scope and iterate solutions.

Lead delivery of a governed agentic AI platform portfolio supporting Markets Operations. Own release calendars, dependency maps, critical paths, risk resolution, migrations, decision records, and executive reporting. Build evidence-based metrics for delivery, platform health, business impact, and agent autonomy. Coordinate engineering, product, controls, design, and operations teams while ensuring safe production releases and audit-ready delivery evidence.

Design and run mixed-methods studies measuring legal teams' real AI proficiency; build and validate surveys/interview protocols; analyze usage and outcome data; translate findings into product, onboarding, and enablement recommendations; communicate results via reports, presentations, and dashboards; prioritize future research.

Lead end-to-end delivery of Payments AI transformation initiatives: plan, govern, and coordinate product and technology delivery, manage cross-functional stakeholders, establish governance, track success metrics, mitigate risks, and drive teams to implement data-driven payment solutions aligned to firm strategy.

Forward Deployed AI Engineers develop Gen AI solutions by building workflows, implementing strategies, and solving real-world problems at scale with clients.

Design, build, test, and deploy scalable AI services integrated with operational systems. Develop Python services, REST APIs, ETL/data pipelines, IaC, and monitoring; collaborate with AI specialists and operations stakeholders to improve workflows, controls, and production readiness in Markets Operations.

Lead end-to-end delivery of AI Agents on the Moveworks ServiceNow platform: design, build, integrate, tune, and launch custom LLM-based automation solutions while partnering with customers, product, and engineering to drive adoption and product feedback.

Lead and mentor an Applied AI team to design, train, evaluate, and deploy large-scale NLP/LLM, graph, and agentic ML solutions; collaborate with business, tech, and control partners; develop firm-wide ML frameworks; research and prototype advanced methods.

Design, build, and productionize autonomous and assistive multi-agent AI systems. Implement RAG and semantic search with vector databases, integrate tools/APIs, apply prompt engineering and guardrails, orchestrate microservices workflows, instrument agents for metrics, run evaluations/A-B tests, and mentor teammates.

Design, build, and deploy scalable ML services combining NLP, CV, and statistical methods. Collaborate with engineers, cloud and SRE teams to productionize models, ensure observability and compliance, and maintain models over time. Communicate results to stakeholders and document processes for regulatory needs.

Lead design and delivery of production-grade LLM and multimodal AI systems. Architect scalable APIs, agentic workflows, and high-throughput microservices. Own end-to-end reliability, performance, and continuous improvement while partnering with ML engineering, product, and cloud teams to deploy secure, enterprise-grade AI at scale.

Lead development and management of agentic AI workbench and control environment, drive integration, deployment, and optimization of agent-led workflows, partner with architecture and engineering, manage risk and KPIs, support stakeholder adoption, and mentor team members to deliver measurable business value across Client360.

Lead technical design and development of AI-native systems for credit pre-trade markets. Build scalable AI platforms, modernize legacy systems, deliver secure production code, partner with trading and product teams, support production operations, evaluate vendors, and drive engineering best practices and communities of practice.

Drive rollout and adoption of AI tools across the Commercial & Investment Bank by persona. Influence product roadmaps, define and report success metrics, enable client-facing teams with training and messaging, track adoption and feedback, and synthesize insights and risks for senior leadership to inform AI product decisions.

Lead design and delivery of enterprise-grade ML systems and production architectures. Build scalable, distributed, data-intensive applications using MLOps and cloud infrastructure (AWS, Kubernetes). Translate research into deployable ML solutions, implement automated pipelines, leverage PyTorch/NumPy and higher-level interfaces, collaborate with SRE/cloud teams, and mentor or optionally manage team members.

Lead development and enhancement of equity derivatives trading and analytics applications, drive automation and AI-assisted engineering practices, collaborate with trading and quant teams, maintain global platform stability, and lead the Systematic Quoting Platform workstream for EMEA.

Lead design and delivery of high-performance, real-time data pipelines and analytics for trading. Drive AI-enabled data engineering, mentor engineers, manage global initiatives, and improve SDLC, testing, and operational reliability.

Lead a technical area driving design, development, and delivery of AI/ML and data platform solutions. Own architecture, governance, and adoption of AI-assisted engineering practices, ensure operational stability, and influence stakeholders while hiring and developing engineering talent.

Lead strategy and delivery of agentic AI across the Commercial & Investment Bank: design, build, and productionize multi-agent systems and RAG pipelines; integrate tools and cloud deployments; implement evaluation, safety, and observability; partner with stakeholders to deliver business impact; and mentor teams on LLMs, agent frameworks, and best practices.

Lead design and delivery of applied AI/ML solutions for data management and governance. Build prototypes, collaborate with business and engineering teams, document models and experiments, present results to stakeholders, and adopt emerging LLM/ML techniques to drive transformation.

Lead applied AI/ML efforts to design, build, deploy, and maintain production ML services (NLP/CV focus). Collaborate with engineering, cloud, and SRE teams, research models, ensure MLOps best practices, and document processes for regulatory compliance.

Lead design and delivery of production-grade AI/ML and agentic solutions for the LLM Suite platform. Own architecture, implementation, and operational stability using public cloud services and agentic frameworks. Build GenAI services, integrate LLMs, ensure secure high-quality code, and improve platform scalability and reliability through collaboration and communities of practice.

Lead AI product strategy and execution for agentic AI pipelines automating bank operations. Define metrics, build demos/prototypes, write PRDs and user stories, and coordinate cross-functional teams to deliver production AI products that meet business goals.

Design, build, and operate LLM inference backend services focused on routing, batching, scheduling, streaming, and quota management. Implement APIs/SDKs, profile and optimize performance (CPU, memory, network, GPU), improve reliability and observability, support CI/CD-safe deployments, and learn LLM serving fundamentals while applying responsible AI and enterprise-authorized AI-assisted development tools.

Lead research and engineering of state-of-the-art ML solutions (NLP, LLMs, recommendation systems). Drive experimentation, design training frameworks, build scalable production deployments, collaborate with cross-functional teams, publish research, and develop firm-wide ML frameworks while adhering to compliance requirements.