Top AI Jobs in Edinburgh

Join Welo Data’s remote Afrikaans contributor network to support AI training projects through text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with compensation and timelines provided before each assignment. This is a talent-community application rather than an active job opening.

Join Welo Data’s Croatian talent network for potential remote AI projects involving text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural or linguistic accuracy reviews. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent community registration rather than an active job opening.

Join Welo Data’s remote Hausa AI contributor network for future projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural accuracy review. This is not an active opening; selected contributors will receive project details, timelines, and compensation when suitable work becomes available.

Join Welo Data’s Basque contributor network for potential remote AI projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent-network opportunity rather than an active job opening.

Join Welo Data’s remote Yoruba AI contributor network based in Nigeria. Projects may involve annotating text, images, or audio; evaluating search results, advertisements, or chatbot responses; creating prompts for large language models; and reviewing cultural and linguistic accuracy. Project duration, scope, timelines, and compensation vary. This is a talent community opportunity rather than an active job opening.

Join Welo Data’s Russian-language AI contributor network for flexible, remote projects involving text, image, and audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Contributors are contacted when suitable projects become available and receive project-specific details about tasks, timelines, and compensation.

Found and operate a scalable enterprise account management motion across hundreds of accounts. Use agentic workflows to assess customer health, prioritize outreach, drive adoption, realize value, support retention and expansion, identify whitespace, and develop reusable playbooks. The role combines customer success, account relationship management, AI adoption, and operational design in a high-velocity environment.

Reviews and evaluates engineering, infrastructure, and platform documents and work products for technical accuracy, completeness, clarity, consistency, and relevance. Provides structured feedback, identifies errors and gaps, compares technical approaches, and follows defined evaluation frameworks. Requires independent work, strong communication, analytical ability, and professional engineering judgment. The role is fully remote and supports varied technical evaluation projects as an independent contractor.

Leads strategic AI ecosystem and NVIDIA-related business development across EMEA. Builds executive, sales, partner, and technical relationships; identifies and influences AI infrastructure opportunities; develops qualified pipelines; supports regional sales teams; provides competitive and market intelligence; and represents DDN at industry and partner events. The role focuses on shaping complex technology opportunities from early engagement through deployment and expanding DDN’s ecosystem reach.

Owns roadmap execution and capability definition for an Agentic AI Platform. Translates AI platform strategy into requirements, prioritized roadmaps, reusable agent orchestration and lifecycle capabilities, governance controls, observability, and scalable platform patterns. Partners with engineering, architecture, data, security, legal, compliance, customer success, professional services, and customers. Measures adoption, reliability, safety, quality, cost, and business impact while balancing technical feasibility, security, compliance, and customer value.

Own the production improvement loop for an AI Context Engine, improving agent behavior, retrieval, memory, telemetry, evaluation, and safe rollout. Build production services in TypeScript or Python, design observability and evaluation systems, analyze agent traces and customer feedback, and partner with data scientists, backend engineers, product, and UX. Mentor engineers, review designs, and shape the technical roadmap for agentic products with public APIs and evolving data models.

Owns revenue for Cohesity’s AI business unit across product, infrastructure, and consulting services. The role generates pipeline, sells AI solutions to executive buyers, develops account plans, delivers business cases, manages enterprise opportunities, and coordinates co-selling with partners such as NVIDIA and hyperscalers. Responsibilities also include CRM hygiene, forecasting, competitive analysis, and building multi-phase customer engagements.

Lead product direction, roadmaps, standards, metrics, and execution for major areas of KIRA’s AI stockbroking app. Guide product managers, product owners, designers, and engineers across multiple squads; balance UX, data, engineering, regulatory, operational, and business considerations; drive launch quality and continuous improvement; and build a high-performing product culture focused on speed, clarity, user value, and measurable outcomes.

Lead product direction, roadmap, standards, and success metrics for major areas of KIRA’s AI neobank app. Guide product managers, product owners, designers, and engineers across multiple squads and financial services, including insurance, payments, savings, investing, and travel. Make product decisions amid regulatory and operational constraints, drive launch quality, measure outcomes, and foster a fast, user-focused product culture.

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.

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.

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.

Build production-grade agentic AI infrastructure for operational automation, including memory, context management, tool-calling, orchestration, evaluation, observability, and feedback loops. Develop reliable LLM workflows, coding-agent systems, and multi-agent architectures while partnering with operational and product teams to automate complex workflows across acquired agencies. Influence architecture, engineering standards, and reusable AI primitives in a remote, early-stage team.

Lead new business development for CounselLink across the UK, managing the full enterprise sales cycle from prospecting through contract execution. Build executive relationships within corporate legal departments, develop enterprise pipelines, deliver product demonstrations, lead RFP responses, negotiate agreements, forecast sales, and identify cross-sell opportunities. The role requires consultative SaaS selling experience, familiarity with legal technology and the UK legal market, and the ability to influence senior stakeholders in a remote, cross-functional environment.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

Lead AI and experience orchestration sales initiatives, supporting account teams with technical expertise, deal strategy, territory planning, customer workshops, proofs of concept, proposals, and executive presentations. Serve as a subject matter expert for AI-powered customer experience and conversational AI solutions, coordinate cross-functional teams, influence opportunity progression, and develop AI-led pathways aligned with customer objectives.