ai engineer for enabling functions

Enfint; Barcelona; Presencial; EUR 120.000 - 160.000; Jornada completa

Descripción de la vacante

AstraZeneca ищет специалиста по архитектуре ИИ и управлению проектами, ответственного за дизайн и реализацию систем с управляемыми моделями в крупной регламентированной среде.

Будет необходима экспертиза в многоагентной архитектуре, соответствие требованиям комплаенса и внедрение устойчивых конвейеров развёртывания, аудит-логов и защиты данных.

Formación

• Опыт создания ИИ-приложений в крупной регламентированной среде.
• Опыт внедрения управляемости и операционной устойчивости в коде и архитектуре.
• Способность превратить идею в работающий PoC за считанные дни.

Responsabilidades

• Проектирование и ведение архитектуры ИИ-решений для функциональных блоков.
• Документирование стратегий моделей, интеграций и инструментов в соответствии с требованиями к продукту и комплаенсу.
• Разработка общих компонентов, паттернов агентов и механизмов аудита и мониторинга.

Conocimientos

AI governance

Multi-agent architecture

Regulatory compliance

MLOps

Educación

Master's degree in AI/CS

PhD in AI (желательно)

Herramientas

Python

Cloud platforms

Terraform

Descripción del empleo

Описание

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.

Задачи

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.

Требования

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.

Условия

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.