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.

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.

Build and maintain backend AI capabilities for GitLab Duo Chat: design flow components and agentic flows in Python/LangGraph, integrate LLMs and multi-agent orchestration, implement and maintain APIs in the Rails monolith, improve observability and reliability, and participate in on-call rotations and cross-functional collaboration to deliver safe, scalable AI chat features.

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.

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.

Lead enterprise sales for Media & Entertainment in the UK: develop market strategies, engage customers and partners, drive adoption of NVIDIA solutions, create references/case studies, identify emerging use cases, and act as NVIDIA's central ecosystem contact to grow business and partnerships.

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.

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.

As an AI Transformation Owner at GitLab, you will shape AI strategies, improve workflows, and drive adoption of AI solutions in your organization, working closely with an AI Engineer.

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.

The role involves leading insights into AI strategies for legal departments, providing unique research and guidance, and engaging with top legal executives on technology adoption and governance.

Lead research and deliver executive-level insights on enterprise AI strategy, producing thought leadership, advising clients and vendors, supporting sales and conferences, mentoring analysts, and driving research agenda and process improvements to accelerate clients' AI value realization.

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.

Lead architecture and delivery of production-grade Generative AI and agentic workflows across frontend (React/TypeScript) and backend (Python/Java/Kotlin/Node.js). Build MCP servers, LLM integrations, evaluation harnesses, observability, caching, and high-availability microservices. Mentor engineers, drive system design reviews, and partner with product to ship scalable GenAI features.

Lead and own enterprise AI platform deployments embedded with clients, delivering time-to-value, reliability, adoption, and scalability. Architect and govern end-to-end AI solutions, run rapid experiments to production, shape strategy and ROI roadmaps for C-level stakeholders, publish reusable blueprints, and manage engineering teams to scale Forward Deployed Engineering capabilities.

Define and lead the enterprise AI operations model, govern model lifecycle (onboarding, deployment, monitoring, retraining, retirement), own AI product performance and reliability, drive cost transparency/optimization across Azure and Databricks, and lead incident, change, resilience, and responsible AI processes to ensure trusted, secure, compliant production services.

Lead technology and AI strategy for the AI Business Solutions practice, focusing on Dynamics 365, Power Platform and Microsoft AI. Define architecture, governance, repeatable Copilot/agent patterns, and technical standards; engage C-suite customers and Microsoft; drive capability investment, IP/accelerators, and senior technical capability development to scale commercially viable AI solutions.

Define and lead the enterprise AI operations model and governance. Own operational performance, monitoring, adoption, reliability, and business value of AI products. Drive cost transparency and optimisation across Azure, Databricks and inferencing. Govern model lifecycle (onboarding, deployment, monitoring, retraining, upgrades, retirement) and lead incident, change, resilience, and responsible AI processes to keep production services secure and compliant.

Manage, prepare and quality-assure exam and assessment data for AI projects. Retrieve, match, anonymise and share data securely with internal teams and third-party contractors, maintain documentation and audit records, and ensure GDPR-compliant handling of datasets.

Lead AI architecture for an agentic LLM assistant (Protege) in PatentSight+. Define AI architecture, evaluate models and platforms, design retrieval/vector search and RAG pipelines, author ADRs, establish prompt engineering and evaluation frameworks, ensure security/privacy/compliance, and partner with product, data, and platform teams to deliver production-grade AI systems.

Lead client engagements to define AI strategy, design enterprise AI platforms and governance, architect secure scalable Generative AI and agent solutions, deliver high-quality roadmaps and designs, mentor teams, and support business development.

Support sales by designing and demonstrating Cisco cloud, data center, and AI-ready infrastructure solutions. Engage customers to assess modernization goals, craft platform architectures, present technical value, run workshops, and collaborate with account teams and partners to drive adoption of compute, storage, networking, and cloud-native technologies.