Top AI Jobs in Manchester

The VP Field Marketing is responsible for leading marketing strategy and execution in Europe, focusing on demand generation, brand awareness, and pipeline development while collaborating cross-functionally and driving a data-driven culture.

Lead AI product strategy and execution for EMEA, building and delivering a portfolio of enterprise AI products that drive measurable business value. Engage executives, shape roadmaps, partner with cross-functional teams, ensure governance and regulatory compliance, and mentor stakeholders to accelerate scaled production deployments and adoption.

Lead a team of controls professionals to translate AI behavior into actionable controls, prototype scalable AI/automation controls, run red-team exercises, steward AI control standards, and engage senior stakeholders to prioritize and deploy AI-enabled control solutions across Asset & Wealth Management.

Lead AI controls enablement by translating AI risks into practical controls, partnering with Controls, Business, and Technology to design scalable solutions, perform risk reviews, implement controls, and advise senior stakeholders to ensure compliant AI adoption.

Design and build GitLab Duo CLI features in TypeScript, shape AI-assisted developer experiences, improve CLI reliability, observability, and performance, collaborate across Developer Clients, and provide technical leadership and mentorship.

The Vice President of Business Process Improvement & Best Practices leads initiatives for process improvement using AI and digital tools, involving cross-functional teams and project management strategies to optimize business processes in finance.

Design and deliver end-to-end features for DAP onboarding and repository/background flows. Build autonomous and scheduled agents that act on customer codebases, improve onboarding experience, collaborate on shared interfaces, review code and designs, and contribute to an async-first, distributed team's technical quality and ownership culture.

Design, build, and operate the high-availability event and trigger system that links GitLab and third-party events to AI-powered Duo Flows. Work in GitLab's Rails monolith, scale for high throughput, influence architecture, add trigger types, collaborate cross-functionally, and participate in Tier 2/3 on-call rotations to troubleshoot production issues.

The Specialist manages data integrity, automation projects, oversees reconciliation processes, leads team performance, and collaborates with operations and technology teams to drive innovations in finance.

Sell an AI-powered recruitment platform: prospect and engage clients, present product features, analyze territory and customers, meet sales targets, collaborate with marketing, and provide regular performance reports while maintaining client relationships.

Own outbound sales for a PropTech AI product: cold outreach, qualify leads, book discovery calls and demos, manage CRM activity, refine sales playbook, and scale into a full-cycle closing role.

Design and implement large-scale AI/ML systems using LLMs and RAG. Develop data pipelines, optimize models, and collaborate with teams on actionable intelligence solutions.

Lead and advise on large-scale technology procurements, outsourcing, cloud/SaaS, AI and digital transformation projects. Draft and negotiate complex technology and commercial contracts, manage multi-stakeholder, multi-jurisdictional matters, supervise junior lawyers, build client relationships, and support business development and market engagement.

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.

As a Staff Backend Engineer at GitLab, you'll enhance backend infrastructure for CI, integrate AI features, and ensure reliability and performance in CI/CD workflows.

Manage the Onboarding Risk team across regions, ensuring high-quality risk decisions, developing team members, and owning onboarding risk procedures. Support complex escalations, collaborate cross-functionally, and keep processes compliant with card scheme rules and payments legislation while improving KPIs and decision frameworks.

Conduct and publish original computer science research (with emphasis on AI and/or cyber security), secure research funding, supervise PhD students, teach and develop inclusive curricula, contribute to departmental administration, knowledge transfer, enterprise and public engagement, and support an inclusive academic community.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Lead field-facing AI security strategy for enterprise customers by designing secure LLM/RAG architectures, delivering demos and POVs, advising on data protection and unsanctioned AI usage, and scaling enablement and product feedback across sales, product, and engineering teams.

The role involves embedding in various parts of the business to identify and solve AI problems, producing working solutions through short sprints, and evaluating their effectiveness while facilitating adoption.

Lead architecture and delivery for Fortives HR technology ecosystem, owning Oracle HCM, Boomi integrations, ServiceNow HRSD, Eightfold and LMS platforms. Define API-first integration patterns, implement AI/automation use cases, ensure data governance and compliance, and guide integration engineers while partnering with HR and IT stakeholders to modernize HR systems.

As an Applied AI Solution Engineer, you will design, build, and deploy AI applications, interact with clients, and solve technical problems, leading teams and ensuring solution quality.

The Principal AI Platform Engineer leads AI architecture design and implementation, guiding teams to deliver secure AI solutions and mentoring engineers.

Senior Azure AI Engineer working in an agile AI squad to design, develop and deploy Azure-based AI solutions — including assistants, copilots, retrieval/RAG systems, cloud-native applications, integrations, security/governance, testing and optimisation — collaborating with analysts, architects and delivery teams to deliver business outcomes.

Design and implement secure, production-ready AI platforms and solutions; move proofs-of-concept to large-scale production; define governance, observability, security and operational standards; support technical discovery, mentor engineers, and develop reusable patterns and accelerators across cloud and data ecosystems.