Top AI Jobs in Edinburgh

Lead global Account Executive enablement by designing and delivering training, coaching, certifications, and sales methodology programs. Improve opportunity progression, conversion rates, deal quality, forecast accuracy, and sales cycle efficiency. Partner with Sales Leadership, Product Marketing, GTM Strategy, Revenue Operations, and regional teams to align programs with business priorities. Drive adoption of AI-assisted selling workflows for research, discovery preparation, stakeholder mapping, deal strategy, and follow-up creation.

Drive pipeline and bookings growth through strategic Global Systems Integrator partnerships across Europe. Develop joint business plans, coordinate enterprise sales pursuits, generate demand, strengthen executive relationships, expand partner-led services and platform adoption, and monitor performance through business reporting. Collaborate with Sales, Marketing, Product, Services, Finance, and alliance teams to execute go-to-market initiatives and deliver measurable revenue outcomes.

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.

Provide technical leadership for production AI and machine learning systems, including generative AI, intelligent agents, predictive modeling, and optimization. Design scalable AI platforms, APIs, services, data pipelines, and infrastructure; establish evaluation, testing, observability, security, and governance standards; optimize system performance, reliability, and cost; and partner with multidisciplinary teams to deploy and operate solutions. Mentor engineers and influence technical strategy across the organization.

Build scalable, full-stack, AI-enabled products for BlackRock’s Aladdin investment compliance and analytics workflows. Lead technical design, implementation, testing, deployment, production support, and continuous improvement. Apply generative AI, semantic search, retrieval, intelligent assistants, and agentic workflows responsibly. Partner with product, engineering, compliance, and business stakeholders to translate complex requirements into deliverable solutions. Influence architecture, champion DevOps and SRE practices, mentor engineers, and promote quality, resilience, security, observability, and maintainability across a global organization.

Identifies high-value AI opportunities, facilitates discovery workshops, translates business challenges into requirements, and manages an AI initiative pipeline. The role requires collaboration with data scientists, technical teams, senior leaders, and subject matter experts. It also contributes to AI adoption strategy, stakeholder engagement, business analysis best practices, and experimental projects addressing financial crime and consumer protection.

Develop, calibrate, validate, and extend soil carbon biogeochemical models for rangeland and grassland regeneration projects. The role quantifies management-driven soil organic carbon changes, integrates field measurements with remote sensing, characterizes uncertainty, and maintains reproducible, version-controlled, audit-ready workflows. It also supports certification, investor and technical due diligence, and produces defensible technical documentation. Collaboration spans UK and US teams across time zones.

Provides technical leadership for production AI and machine learning systems, including generative AI, intelligent agents, predictive models, and optimization. Establishes architecture, engineering standards, evaluation and observability practices, and reusable AI platforms. Partners across business, engineering, data, risk, and control teams to deploy and operate scalable systems while optimizing performance, reliability, security, and cost. Mentors engineers and influences technical strategy.

Leads flagship AI Labs initiatives from scoping and research through production deployment. Designs and evaluates AI agents and agentic workflows, guides production-grade architecture, establishes quality and safety measurement, and partners with business and engineering stakeholders. Manages and mentors 3–6 AI scientists while communicating technical outcomes to senior leaders and broader audiences.

Conducts research on AI-enabled turbulence computation by designing, training, and releasing large neural network models for embedding and predicting high-Reynolds-number turbulent flows. The role applies graph neural networks, transformers, and dynamical systems theory, collaborating with academic researchers, industrial partners, and a major technology company. The position is full-time, fixed-term for 36 months, and includes opportunities for industrial collaboration and career development.

Conduct research on AI risk, algorithmic assurance, and insurance. Develop mathematical, statistical, and computational methods to evaluate, price, monitor, and mitigate AI-related risks. Build reproducible code, simulations, benchmarks, and evaluation tools; publish findings; present at conferences and industry workshops; collaborate with academic and industry partners; and support workshops, reports, grant development, and stakeholder engagement.

Develop and implement policy for responsible innovation, digital firms, emerging technologies, and personal data use. The role involves researching complex regulatory issues, providing data protection advice, influencing senior stakeholders, coordinating cross-organisational projects, identifying emerging risks, supporting regulatory supervision, and building relationships with businesses, innovators, regulators, and other organisations. The postholder will also represent the ICO at meetings, workshops, conferences, and regulatory forums in the UK and internationally.

Lead Standard Life’s digital and CRM vision, strategy, roadmap, and product ownership practice. Drive connected, personalized customer journeys across digital, voice, messaging, adviser, employer, and colleague channels. Partner with business, data, engineering, risk, compliance, and strategic teams to deliver measurable customer, commercial, and operational outcomes. Champion customer data, personalization, next-best-action, journey orchestration, and AI-enabled engagement while influencing executives, boards, governance forums, and prospective clients.

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.

Owns the full data-product lifecycle, including retail data imports, integrations, pipelines, metrics, reporting APIs, AI agents, and dashboards. Sets roadmap priorities, conducts retailer discovery, partners with engineering and data teams, validates product adoption, and uses SQL and analytics to measure business impact. Requires strong technical depth, enterprise customer communication, cross-functional execution, and occasional travel for store and customer visits.

Leads the design and delivery of cybersecurity and fraud analytics solutions using Databricks, Python, SQL, R, AI/ML, LLMs, and computer vision. Directs data science, data engineering, and BI teams; manages concurrent engagements; investigates emerging threats; integrates new data sources; communicates findings to stakeholders; recommends remediation; and applies MLOps and model lifecycle practices in secure federal environments.

Conduct research, market sizing, forecasting, competitive analysis, and thought leadership on enterprise AI services. Develop actionable insights for technology providers and senior executives through published research, presentations, conferences, and client engagements. Assess market trends, demand drivers, customer behavior, and growth opportunities while advising clients, supporting sales, reviewing content, mentoring analysts, and improving research processes.

Lead consulting, discovery, advisory, and shaping engagements for Microsoft Business Applications, Power Platform, Copilot, and AI-enabled business processes. Facilitate stakeholder workshops, assess services and processes, define requirements and roadmaps, shape operating models and governance, establish value measures, and guide adoption and organizational change. Collaborate with multidisciplinary teams while advising on responsible AI, privacy, security, regulatory, and human oversight considerations. Contribute to proposals, business development, reusable consulting assets, coaching, and people management.

Own AI stockbroking and other financial-services product areas from user-problem discovery through launch and iteration. Define product direction, scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial workflows; use research, feedback, experiments, and performance data to improve products; and balance speed, user experience, business impact, compliance, and operational complexity.

Senior individual contributor producing thought leadership and pragmatic insights on enterprise AI and emerging technologies. Advise C-suite, research market trends, create presentations, support sales and peer review, mentor junior analysts, and drive research process improvements while engaging clients and presenting at industry events.

Own the end-to-end product strategy and execution for an AI-powered email application. Define AI behavior, system requirements, evaluation frameworks, quality standards, and user experiences while balancing reliability, latency, cost, safety, and usability. Partner closely with ML, backend, and client engineering teams to identify failure modes, improve system performance, prioritize work, and deliver predictable, trustworthy AI capabilities in a fast-moving zero-to-one environment.

Own the end-to-end product direction and quality of an AI-powered email application. Define AI behavior, system requirements, evaluation frameworks, quality standards, and user experiences while balancing quality, latency, cost, reliability, safety, and usability. Partner closely with ML, backend, and client engineers to identify failure modes, prioritize improvements, run experiments, and deliver predictable, trustworthy AI features in a fast-moving zero-to-one environment.

Lead application engineering for an AI email product across backend, mobile, and desktop platforms. Design reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Build APIs connecting AI capabilities to product experiences, guide a senior engineering team, make architecture and reliability trade-offs, and establish observability, monitoring, testing, and operational excellence. Partner with ML leadership to ship scalable, maintainable, and high-performing AI-powered experiences.

Own the end-to-end product direction and quality of AI-powered systems. Define requirements, evaluation frameworks, quality bars, and feedback loops while balancing model quality, latency, cost, reliability, safety, and user experience. Partner deeply with ML, backend, and client engineers on system design and iteration, identify failure modes, and drive execution in a fast-moving zero-to-one environment.

Own end-to-end data science solutions, including problem framing, feature and data structure design, experimentation, model development, deployment, monitoring, validation, and retraining. Write robust production-quality Python and SQL, communicate findings to technical and non-technical stakeholders, follow data governance and responsible AI standards, mentor junior colleagues, and improve modelling and engineering practices.