Top AI Jobs in Edinburgh

As the primary engineer for Aperture OS, you will own the full codebase, drive feature development, manage API and AI integrations, and ensure security and scalability in a multi-tenant SaaS environment.

Build and ship AI-native systems for a fintech neobank: AI agents, RAG/LLM apps, tool-calling and automations to improve onboarding, KYC, support, risk review, CRM and operations, focusing on reliability, latency, cost, security and compliance while collaborating with product and engineering teams.

The role involves creating research content, providing insights in Analytics and AI, engaging with clients, and mentoring team members. A strong focus on industry trends and effective presentation skills is required.

Design, build and optimise Python-based AI applications and data storage solutions. Collaborate with clients and teams, enforce code quality, CI/CD, testing practices, and deliver scalable production systems across cloud environments while travelling to client sites.

Architect and build a production, self-improving learning platform: capture event pipelines, measure outcomes, implement recommendation and feedback loops, maintain knowledge graphs and vector stores, build feature stores and experimentation infra, and create evaluation frameworks. Spend majority time coding and shipping resilient systems while providing technical leadership and shielding the engineering team.

Lead design and implementation of scalable AI-centric systems for offensive security, develop agentic AI capabilities (LLMs, RAG), own feature lifecycle to production, mentor engineers, run design reviews, and integrate AI into microservice architectures with cloud, container, and messaging technologies.

Design, build, and deploy AI systems (predictive models, NLP, generative AI) from PoC to production. Work with clients to define use cases, prepare large datasets, implement deployment and monitoring pipelines using cloud-native tools, and collaborate with cross-functional teams to operationalize AI solutions.

The AI Business Development Manager will engage with clients, identify sales opportunities, manage client relationships, and convey complex AI standards and services effectively.

The Research Manager will lead AI-powered insight projects, manage client relationships, oversee team execution, and innovate using AI tools to improve insights delivery.

Senior commercial role to originate, qualify, and convert GPU compute demand across Armada's AI factory and Leviathan deployments. Build and manage a pipeline of offtake, anchor tenancy, and reserved capacity deals; map customer requirements to deployable infrastructure; shape commercial structures and go-to-market; and provide market intelligence to inform site selection, capacity planning, and product strategy.

Build and ship AI-driven GTM systems: outbound lead engine, inbound/lifecycle automations, AI-assisted content pipeline, data/reporting layer, and fast production patches to eliminate manual marketing workflows.

As a Senior Python Backend Engineer at VidRush, you'll build AI-driven video production systems, ship production-level ML/LLM services, and work closely with product teams while ensuring high autonomy and delivery speed.

Lead development of an autonomous agentic AI scientist for drug discovery: architect multi-step reasoning agents, bridge AI and wet-lab experiment design, prototype to productionize agentic systems, publish research, and collaborate with biological experts.

Drive the expansion of software development and AI services by managing client relationships, building sales pipelines, and negotiating contracts.

Design and build scalable AI platform capabilities on Azure and Databricks, produce technical designs, develop reusable platform components, optimize performance/cost, and collaborate across engineering, architecture, and product teams to deliver model hosting, data integration, APIs and enterprise-grade platform services.

Lead design and build of scalable AI platform capabilities on Azure and Databricks, including data lakes, integration, model hosting, APIs, and IaC. Produce technical designs, reusable platform components, optimize performance/cost, and collaborate across engineering, architecture, and product to drive operational excellence.

Design end-to-end AI experiences for consumer and enterprise products: research opportunity areas, prototype agent behaviour/personality, craft UI/UX and brand-aligned visual expression, and work with engineering to build testable, trustworthy AI solutions.

Author and iterate curriculum for experienced engineers transitioning to system architecture: validate syllabus, define measurable learning objectives, produce and fine-tune lessons with AI tools, design hands-on projects and rubrics, respond to LX feedback, and deliver milestone-based content over a 4–6 month, 15–20 hr/week engagement.

Lead enterprise sales for Everpure's AI/HPC data infrastructure, driving large deals with F1000 companies. Build executive relationships, lead cross-functional pursuit teams, influence product roadmap, manage a pipeline to exceed revenue targets, and evangelize all-flash storage and data pipeline solutions for AI workloads.

Customer-facing AI engineer delivering and productionizing GenAI applications (RAG, multi-agent, Text2SQL, fine-tuning). Own production rollouts, advise customers, present at conferences, and collaborate with product and engineering to shape roadmap and influence priorities.

Facilitate workshops to define AI/agent use cases, design and deploy Copilot Studio agents integrated with Power Platform and enterprise data, test and iterate solutions, enable scaling and governance, and provide documentation, training, and stakeholder engagement to drive adoption.

Build core AI platform capabilities (agent runtimes, model routing, tool registries) and production-grade services and tooling using Node.js, TypeScript, NestJS and React. Develop reusable AI infrastructure, work with LLMs and LangChain/LangGraph, and own features end-to-end to enable secure, scalable AI across the company.

Operate from the CEO Office to translate CEO priorities into execution across product, hiring, licensing, partnerships and market launches. Track OKRs, owners, decisions and blockers; prepare briefs and action trackers; coordinate cross-functional teams; identify and close execution gaps; and own urgent business problems that cut across departments.

The Software Engineer will shape AI governance in developer tooling, build product features, collaborate with teams, support users, and innovate rapidly.

Lead AI security technical strategy across customers and field teams. Serve as senior SME in AI security, run discovery workshops, design demos/POVs, create reusable reference architectures, and influence product, PMM, and engineering using field insights. Support strategic engagements, enablement, and thought leadership to scale AI security adoption.