Top AI Jobs in Edinburgh

Serves as the primary technical advisor for strategic enterprise customers, guiding platform optimization, architecture, integrations, security, reliability, and feature adoption. Conducts technical health reviews, identifies risks, troubleshoots complex integration issues, develops technical success plans, and delivers training and workshops. Acts as the technical liaison between customers and internal product, engineering, and support teams while advising on compliance, authentication, data protection, and scalable cloud architectures.

Partner with customers after the sale to deploy, integrate, and optimize AI security solutions across cloud, on-premises, and hybrid environments. Provide technical guidance on Docker, Kubernetes, cloud networking, and infrastructure as code; troubleshoot issues; deliver training and documentation; and serve as the primary technical contact. Capture customer feedback and collaborate with product, engineering, and research teams to improve products and support successful scaling.

Own the end-to-end technical customer relationship for Arango’s AI product suite, from discovery and architecture through production deployment and expansion. Design graph, multi-model, GraphRAG, vector retrieval, agent, data pipeline, observability, security, and compliance solutions. Build prototypes, guide customer engineering teams, establish evaluation and monitoring practices, document reusable patterns, and provide product feedback. The role requires deep graph expertise, applied AI and Python skills, cloud and infrastructure experience, and excellent executive-to-engineering communication.

Lead research and advisory on application security for enterprise applications (ERP/CRM). Produce thought leadership, client-facing insights, presentations, market analysis, and support sales. Mentor analysts, drive research agenda, improve processes, and advise CIOs on security strategy, vendor evaluation, metrics, and vulnerability testing across major vendors (SAP, Salesforce, Workday, Oracle).

Design and build GitLab Duo CLI features in TypeScript, shape AI-assisted developer experiences, improve CLI reliability, observability, and performance, collaborate across Developer Clients, and provide technical leadership and mentorship.

Build and maintain production REST APIs using Java 21 and Spring Boot while developing AI-powered portal features with Python on GCP. Responsibilities include creating MCP and agent tooling, shipping LLM-backed products, managing Kubernetes and cloud services, modernizing legacy Java systems, conducting code reviews and testing, and advancing AI-assisted development practices across the engineering team.

Build AI-powered features that automate data-driven slide decks and documents. Develop production LLM solutions using LangChain, RAG, LlamaIndex, and generative AI technologies; improve system performance and reliability; and collaborate with designers and engineers. Responsibilities span AI insights, content generation, integrations, optimization, and potentially LLM agents. The role requires advanced Python, machine learning and NLP expertise, and experience building and fine-tuning LLMs in production.

Build and ship AI-powered internal tools quickly using LLMs, agent frameworks, and embedding pipelines. Integrate models, APIs, databases, and third-party services; deploy and monitor production solutions that automate company workflows and scale reliably.

Leads AI and automation initiatives across portfolio companies, partnering with executives to identify process improvements, build and deploy prototypes, manage technology partners, develop business cases, and scale reusable solutions. The role requires hands-on workflow automation, prompt engineering, RAG fundamentals, Python, and stakeholder management experience.

Drive end-to-end B2B sales of Data and AI consulting services in the US market. Responsibilities include prospecting, pipeline generation, solution selling, account planning, business-case development, executive stakeholder engagement, partner collaboration, and closing enterprise and mid-market opportunities involving Databricks, Lakehouse modernization, data engineering, analytics, AI/ML, and GenAI.

Supports the design, development, and deployment of applied AI systems under senior engineer guidance. Contributes to AI feature development, follows engineering standards, participates in code reviews and technical discussions, and builds expertise across modern AI and cloud technologies. The role emphasizes learning, collaboration, and progression toward more senior engineering responsibilities.

Build and operate Typeform’s internal AI Operations capability for R&D. Identify and prioritize AI opportunities, discover workflows, design and deliver AI-native solutions, and manage their lifecycle after launch. Responsibilities include improving enterprise AI tools, coordinating access and governance, evaluating reliability and security, supporting automations and agents, measuring adoption and value, and partnering with Product, Engineering, IT, InfoSec, Finance, and other teams.

Lead discovery, rapid prototyping, and deployment of production-ready AI solutions for supply chain and manufacturing. Build Python-based RAG pipelines, semantic search, multi-agent workflows, data integrations, and enterprise platform connections. Engage frontline operations, translate business needs into technical requirements, manage agile delivery, and ensure prototypes are scalable and transferable to core engineering teams. Work across SAP, MES, shop-floor platforms, databases, telemetry, and unstructured data while collaborating with security, data, and architecture teams.

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.

Coordinates the AI Accountability Network’s newsletters, training programs, grants, fellowships, payments, events, communications, and community initiatives. Manages editorial workflows, contractors, applications, logistics, websites, listservs, dashboards, metrics, and stakeholder communications. Supports grant administration, funder reporting, travel, curriculum development, and website publishing while improving processes and tracking program impact.

Build and refine AI-powered prototypes for supply chain and manufacturing operations. Engage with factory and warehouse teams, translate operational needs into software requirements, develop Python-based RAG and agentic systems, integrate APIs and data sources, and iterate prototypes based on frontline feedback. The role involves SQL and document data preparation, agile collaboration, occasional manufacturing-site travel, and progressive adoption of enterprise AI frameworks and production engineering practices.

Leads customer-facing Frontier AI projects from architecture through production deployment. Oversees integrations of Actonomy products in customer environments, guides Forward Deployed Engineers, manages and mentors staff, and partners with senior stakeholders. Translates customer needs into product improvements, creates reusable implementation assets, supports AI adoption, and communicates architectural and commercial decisions to technical and nontechnical audiences.

Join Welo Data’s Canadian French contributor network for potential remote AI projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and details provided before each assignment.

Join Welo Data’s French AI Trainers Network as a flexible contributor supporting annotation, evaluation, and prompt creation projects. Contributors may label text, images, or audio; assess search results, advertisements, and chatbot responses; create prompts for large language models; and ensure cultural and linguistic accuracy. This is a talent community rather than an active opening, with project details and compensation provided when assignments become available.

Build production AI agents and integrations for Customer Success, Sales, and Operations. Translate manual workflows into high-value automations, connect LLMs with internal databases and SaaS tools, implement human approval gates and guardrails, manage reliable asynchronous integrations, and evaluate agent accuracy, hallucinations, latency, and cost. The role requires strong Python or TypeScript skills, Claude expertise, agent tool design knowledge, SaaS API experience, and effective collaboration with nontechnical teams.

Lead the end-to-end product experience across acquisition, onboarding, avatar selection, chat, media generation, and retention. Drive conversion, retention, and LTV through hypotheses, prioritization, A/B testing, and data-informed design. Establish the product’s design direction and design system, lead a multidisciplinary design team, and partner with product, analytics, marketing, engineering, research, and support.

Drive AI Native co-sell initiatives across EMEA, particularly the UK, by coordinating NVIDIA sales and partner ecosystems. Build strategic business relationships, track alliance revenue and offtake, develop scalable operational frameworks, analyze market trends, and position NVIDIA offerings with cross-functional teams.

Own Anaconda’s design system across Figma, design tokens, documentation, and production code components. Lead migration to shadcn/ui and Storybook, establish governance and release processes, and create AI-forward patterns for agentic product experiences. Partner closely with engineering, prototype in TypeScript and React, review AI-generated code, and influence a senior design team through critique and pairing.

Conduct independent AI research focused on evaluation methodologies, alignment techniques, and synthetic data generation. Design rigorous experiments and scalable frameworks for evaluating LLMs and agent systems using human data. Build research infrastructure and practical tools, applying fine-tuning, optimization, quantization, adapters, and distillation. Publish research, contribute to open source, collaborate with engineering and product teams, mentor colleagues, and communicate complex AI concepts clearly.

Contribute to AI data projects through language data annotation, evaluation, and instruction creation. Work remotely with flexible hours to help develop more inclusive and capable AI systems. Applicants must be native or near-native Simplified Chinese speakers living in China, Canada, the United States, or Malaysia, with fluent English, comfort using digital tools, strong attention to detail, and curiosity.