Top AI Jobs in Edinburgh

Own product areas for an AI neobank across financial services such as insurance, payments, savings, investing, and travel. Define product direction, user problems, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, compliance, operations, and business teams; simplify complex financial journeys; and use research, feedback, experiments, and performance data to continuously improve products.

Own product areas within AI Stockbroking and broader financial services. Define user problems, product direction, scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams. Simplify complex financial products, use research and performance data to guide decisions, launch features quickly, and drive continuous post-launch iteration while balancing user experience, business impact, compliance, and operational complexity.

Own product areas within BJAK’s AI Neobank across financial services such as insurance, payments, savings, investing, and travel. Define user problems, product direction, roadmaps, metrics, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; and use research, feedback, experiments, and performance data to drive continuous improvements.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related financial services. Define user problems, product strategy, roadmaps, metrics, launch plans, and customer journeys. Collaborate with engineering, design, data, operations, compliance, and business teams to ship features quickly, monitor performance, and iterate using data, research, feedback, and production insights. Balance user experience, business impact, compliance, operational complexity, and delivery speed.

Own product areas across AI investing and other financial services. Define user problems, product scope, success metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial products; launch features; monitor performance; and iterate using data, feedback, research, and production insights.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; launch features; monitor performance; and iterate using data, feedback, research, and production insights.

Own AI engagement outcomes from success definition through production delivery. Design and evaluate end-to-end AI and GenAI systems, manage technical risk and trade-offs, communicate with clients, lead code reviews, resolve technical disagreements, mentor engineers, and develop reusable components and best practices. Deploy models and LLMs on AWS or Databricks with strong testing and CI/CD practices.

Industry Expert who sets the technical bar for advanced AI, ML, systems, or forward-deployed engineering programs. Responsibilities include reviewing deployed projects, leading technical defenses and mock review boards, delivering occasional live sessions, critiquing architecture and tradeoffs, and advising instructors on difficult design decisions. The role requires production-scale engineering experience, senior-level judgment, a public technical footprint, strong English, and comfort with AI tools. It is fully remote and requires approximately 4–10 hours monthly.

Own the AI architecture for an agentic patent-analysis assistant, defining scalable systems for reasoning, retrieval, semantic search, data enrichment, prompt engineering, evaluation, and LLM quality. Partner with engineering, product, data, security, and platform teams to shape the roadmap and ensure enterprise-grade security, privacy, reliability, observability, cost governance, regulatory compliance, and Responsible AI alignment. Document architectural decisions and communicate technical strategies to technical and executive stakeholders.

Develop and scale NVIDIA Inception’s European startup ecosystem by identifying, technically assessing, recruiting, enabling, and nurturing AI and accelerated-computing startups. The role advises founders and technical leaders on CUDA, NVIDIA SDKs, AI frameworks, GPU infrastructure, and platform adoption; leads technical workshops; translates ecosystem feedback into product insights; collaborates with venture capital firms and internal teams; and supports sales and enterprise customer motions. Travel across Europe is required approximately 40% of the time.

Leads the identification, development, testing, and scaling of AI and automation solutions across internal delivery processes and future customer-facing use cases. Builds automated test suites, scripts repetitive workflows, pilots generative AI and agentic tools, creates reusable automation assets, tracks measurable value, and enables teams through training and knowledge sharing. Collaborates with project managers, product owners, process owners, testing communities, and delivery teams to ensure maintainable, responsible, and broadly adopted solutions.

Lead and scale an EMEA team of AI and experience orchestration overlay sellers. Coach specialists, establish operating models, drive AI-focused sales motions, partner with Account Executives and sales leadership, support strategic enterprise opportunities, and translate customer challenges into AI use cases and measurable value. Monitor market and competitive trends while collaborating with Product, Marketing, Enablement, Customer Success, and Professional Services to improve go-to-market effectiveness.

Owns NVIDIA’s EMEA go-to-market motion for its Agentic AI Platform. Drives customer and partner adoption across enterprise, AI-native, cloud, public sector, defense, and regulated environments. Develops sales enablement, reference architectures, field guidance, and adoption strategies covering open models, security, governance, deployment, licensing, and confidential computing. Coordinates with technical, product, legal, security, engineering, and ecosystem teams while translating complex AI platform capabilities into commercially effective sales plays and revenue outcomes.

Lead full-stack development for a legal AI platform: design intuitive UIs and robust backends, integrate AI/LLMs with applications, architect scalable systems, mentor junior developers, collaborate with AI researchers, and automate systems for efficiency.

Senior AWS consulting leader advising enterprise clients on cloud, data and AI strategy. Lead discovery workshops, shape large-scale transformation programmes, design cloud-native roadmaps, support pre-sales, mentor architects, represent the firm externally, and ensure strategic intent translates into delivery.

Partner with investment teams to identify high-value AI use cases, design lightweight proofs-of-concept, enable users through training and best practices, provide light technical support, and track adoption and impact of AI solutions across EMEA research teams.

Manage multilingual data collection and Large Language Model evaluation projects, ensuring quality assurance and effective global team coordination.

Join Verve as an Insight Associate, focusing on AI-powered market research. Learn to design research, interpret human behavior, and contribute to client projects using AI tools.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Own the end-to-end UX for an AI assistant across iOS, Android, and web. Design user flows for AI-assisted tasks, including intent capture, progress tracking, confirmations, error recovery, and varied AI states. Conduct usability research, create wireframes and high-fidelity Figma designs, collaborate with product, engineering, and ML teams, and contribute to shared design patterns and systems.

Own product areas across an AI-driven neobank app (payments, savings, investing, insurance, travel). Define problems, roadmap, success metrics; work with engineering, design, data, operations, compliance and business teams. Launch features, monitor performance, iterate using data and user feedback. Balance speed, UX, business impact and compliance while driving execution.

Lead product direction and execution for major AI neobank app areas. Define roadmaps, priorities, metrics, and product standards across squads. Guide PMs, designers and engineers; balance strategy, UX, data, engineering and business outcomes. Work across insurance, payments, savings, investing and travel; translate regulatory and operational constraints into practical product decisions. Drive launch quality, post-launch learning, and continuous improvement while building a fast, measurement-driven product culture.

Lead design and implementation of high-performance agent runtimes, backend services, and self-hosted model/agent infrastructure. Build low-latency execution systems, real-time data pipelines, telemetry loops, CI/CD for zero-downtime deployments, and ensure fleet reliability on AWS/EKS.

The AI Creative Designer creates high-quality, AI-generated visuals for marketing campaigns, collaborating with teams to optimize visual content for conversion rates.

Lead budgeting, forecasting, and variance analysis while building AI-driven financial models, scenario planning, KPIs, and dashboards. Automate FP&A processes, deliver insights to senior leaders, and collaborate with cross-functional teams to improve forecast accuracy and strategic decision-making.