Top AI Jobs in Edinburgh

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.

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.

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.

Lead EMEA Employee Relations, Labor Relations, and HR Generalist services. Define regional strategy, manage Works Council and union relationships, oversee investigations, optimize hybrid service delivery, drive transformation, implement data-driven tracking and AI-enabled insights, and partner with HR COEs and business leaders to support M&A and growth.

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.

The Senior AI Engineer will design, build, and deploy generative AI systems, collaborating with clients to drive AI adoption and deliver business impact in financial services.

Lead product strategy and roadmap for a hospitality platform used across product suites. Build and develop a Product Management team, prioritize platform work with engineering, and drive shared capabilities (data, integrations, AI) to create reliable, scalable services that deliver commercial and customer value.

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 the design and development of generative AI systems, focusing on LLMs and MLOps pipelines within financial services, guiding teams in strategic AI adoption.

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.

Lead and scale multi-team AI engineering and data science organization to design, deliver, and govern GenAI, LLM, Vision AI, and multi-agent knowledge products; own end-to-end solution design, Agile delivery, quality standards, production validation, stakeholder alignment, hiring, and organizational capability building.

Ownership of backend features for Agentic Tools: design and implement GraphQL/REST APIs, build secure scalable Ruby on Rails services, improve RSpec automated tests, collaborate across product and AI teams, participate in Tier 2 on-call, and shape architecture for AI agent interactions with GitLab.

Lead and scale an AI Security incubation team to drive technical GTM strategy, recruit and mentor principal AI security specialists, enable global sales with repeatable POVs and playbooks, advise Fortune 500 C-levels on safe AI deployments, and feed field insights into Product and Engineering to drive revenue growth.

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.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

As a Senior Product Manager, you will define and evolve GitLab's AI Platform Management capabilities, focusing on AI Control Plane and strategic governance. You'll lead product discovery, drive stakeholder alignment, and collaborate across teams to deliver effective management solutions for AI usage.

As an AI Subject Matter Expert, you will guide the application of AI in core DevOps, partnering with stakeholders to enhance developer productivity and software delivery.

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.

Lead design, build, deploy, and maintain production-grade AI/ML systems for the Economic Crime Hub. Own end-to-end model lifecycle, ensure compliance and explainability, establish MLOps standards and tooling, build scalable AI platform architecture, and hire and develop a high-performing ML engineering team.

Lead the Data Science and AI agenda for the Economic Crime Hub, designing, building, and deploying production-grade models, LLMs, and agentic workflows. Own end-to-end model lifecycle, embed controls, MLOps, monitoring, and governance, and scale automated decisioning solutions. Build and manage a multidisciplinary team of Data Scientists, ML Engineers, and MLOps specialists while partnering with Product, Technology, and Model Risk to ensure explainability, auditability, and compliance in a regulated environment.