Digital Platforms Ai System Engineer

Astrazeneca - Barcelona, Catalonia, Spain

Skip to main contentIT Managementalexion logo Search jobs DIGITAL PLATFORMS AI SYSTEM ENGINEER Location Barcelona, Catalonia, Spain Job ID R-237952 Date posted 03/03/2026 INTRODUCTION TO ROLE: This role is based in Barcelona, with an on-site commitment of three days a week. Fluency in English is required. As a Digital Platforms AI System Engineer(AI & Agentic CMS Automation), you’ll drive the next wave of digital delivery by embedding AI and agentic automation into our content management and web engineering ecosystem. The focus of this role is not “more CMS customization”—it’s making the CMS and delivery workflows smarter, faster, and safer through LLM-powered assistants, autonomous/agentic workflows, and AI-augmented developer experience. You will lead initiatives that automate content operations end-to-end: from brief-to-draft generation and structured content enrichment, to governed publishing, personalization experimentation, and AI-assisted site operations. You’ll partner closely with product, platform owners, legal/compliance, and engineering teams to design and implement secure, compliant AI patterns that improve quality and reduce time-to-market. While experience with Sitecore or similar remains relevant, we’re intentionally prioritizing candidates with strong AI implementation experience and a proven ability to integrate AI capabilities into real production systems. ACCOUNTABILITIES: AI-first CMS enablement: Design and deliver AI capabilities that augment CMS workflows (content creation, tagging, summarization, translation support, content QA, link integrity checks, SEO recommendations, accessibility checks, and publishing readiness). Agentic automation in the CMS space: Build and orchestrate agentic workflows that can plan and execute multi-step tasks (for example: “create a campaign landing page,” “refresh product content across locales,” “validate regulatory rules,” “generate structured components,” “create PRs,” “open approvals,” and “publish”). LLM-powered developer productivity: Improve engineering throughput via AI-augmented coding, review, test generation, release notes, and incident response playbooks; embed these safely into CI/CD and SDLC practices. AI search and conversational experiences: Implement intelligent site search and conversational interfaces grounded in approved content sources (RAG-style patterns), including monitoring for quality, drift, and safety. Content intelligence & personalization: Enable content insights (performance summarization, intent detection, taxonomy suggestions) and support experimentation/personalization frameworks with clear governance. Architecture & integration leadership: Define patterns for integrating LLMs and AI services with CMS, DAM, analytics, and delivery channels via APIs and event-driven approaches. Governance, compliance, and safety: Implement robust generative AI governance (auditability, human-in-the-loop approvals, prompt/version management, data handling, risk controls, and security-by-design). Operational excellence: Ensure observability and reliability of AI-enabled features (telemetry, evaluation, tracing, cost controls, incident management, fallback strategies). Cross-functional delivery: Collaborate with product managers, platform owners, and stakeholders to translate business needs into secure, scalable AI-enabled solutions. Technical mentorship: Coach engineers on AI patterns, agentic workflow design, modern web architecture, and delivery discipline. ESSENTIAL SKILLS/EXPERIENCE: Senior engineering experience: 6+ years in software engineering with significant experience delivering production web platforms; ability to lead technical deliver...