ai engineer for enabling functions

AstraZeneca is a pharmaceutical manufacturing company that combines data, analytics, AI, modern engineering, and science to support the development of life-changing medicines and enable global business functions.

• Lead end-to-end technical design and solution architecture for AI systems across enabling functions;
• Make and document model strategy, integration, and tooling decisions against product and compliance requirements;
• Identify and build shared components, reusable agent patterns, and governance instrumentation;
• Implement model routing, data residency, and hosting decisions that respect jurisdictional boundaries;
• Design and ship multi-agent LLM systems across providers with sovereignty-aware routing and human-gated controls;
• Build governed RAG pipelines with hallucination guards and immutable audit logging;
• Deliver proof-of-concepts in days with progression gates to pilot and production;
• Implement governance-as-code components, approval workflows, monitoring, oversight, routing layers, model and data cards, and audit trails;
• Engineer systems for data protection laws, AI regulations, and sector-specific operational resilience requirements;
• Build resilience through circuit breakers, provider fallbacks, graceful degradation, fail-safe defaults, failover paths, and chaos testing;
• Own delivery from design through production, scaling, monitoring, and lifecycle management;
• Establish CI/CD, automated testing, performance monitoring, incident response automation, and capacity management;
• Build data pipelines, feature stores, and data products with quality, governance, lineage, and controls;
• Implement drift and bias monitoring, lead AI red-teaming, embed fairness and explainability pipelines, and produce assurance reporting;
• Adapt solutions across business functions and integrate external partners at a technical level;
• Run technical discovery, prototype quickly, iterate on UX, and measure adoption and impact through KPIs and KRIs;
• Represent delivery in architecture and AI leadership forums, contribute to enterprise governance and standards, and share reusable patterns.

• Built AI applications inside a large, regulated enterprise;
• Delivered AI solutions across HR, Finance, Procurement, Legal, Audit, or Compliance;
• Significant experience implementing governance controls and operational resilience in code and architecture;
• Ability to move from an idea to a working proof-of-concept in days;
• Deep expertise in AI governance, operational resilience, and regulatory compliance;
• Technical authority in multi-agent architecture, production coding, RAG pipelines, and governed AI applications;
• Experience implementing multi-jurisdictional data sovereignty, regulatory divergence, and cross-border AI governance requirements;
• Proficiency in foundation models, fine-tuning, multi-provider orchestration, RAG, and sovereignty-aware model routing;
• Leads through mentorship, code quality, and engineering standards while remaining a strong individual contributor;
• Nice to have: Shared libraries, reusable agent frameworks, governance middleware, common instrumentation, AI-assisted development, MLOps, fairness testing, explainability pipelines, AI red-teaming, assurance reporting, resilience engineering, classification and tiering logic, model registration, approval workflow automation, monitoring pipelines, lifecycle decommissioning controls, enterprise technology and data engineering partnerships, KPI/KRI design, UX-driven iteration.

• The role requires working from the office an average minimum of three days per week;
• Flexible arrangements are available around the office expectation;
• Technology directly supports life-changing medicines;
• Opportunities include experimentation with leading-edge platforms, collaboration with diverse experts, hackathons, and external partnerships;
• The company supports diversity, equality of opportunity, and inclusive hiring.