Senior Director, AI Engineering, Enabling Units

Senior Director, AI Engineering, Enabling Units

Barcelona, Spain

Competitive salary and benefits

Introduction to role 

This senior engineering leadership role is accountable for the technical strategy, architecture, team performance, and production delivery of AI solutions across AstraZeneca’s Enabling Functions – Legal, Procurement, Finance, Business Development, Audit, and Compliance. The focus is on owning and executing the engineering vision, not programme management. The Senior Director builds and leads high-performing engineering teams, sets technical standards, and works closely with EA IT and Data teams, internal stakeholders, and external partners to scale AI from opportunity identification through to enterprise-wide impact. The role delivers scalable, production-grade AI systems in environments where regulatory sensitivity, data integrity, and operational resilience are essential. How will AI reshape the way a global company contracts, spends, reports, audits, and stays compliant? This role leads that transformation.

Accountabilities 

Lead the multi-year engineering strategy for AI across Enabling Functions, aligning architecture, team capability, and delivery sequencing with business priorities and value. Define and evolve a modular, reusable AI platform architecture that supports cross-functional use cases from day one, enabling rapid reuse of components such as document intelligence, risk scoring, and forecasting. Make high-consequence technical decisions on build-versus-buy, model strategy (including foundation models, fine-tuning, and RAG), integration patterns, and platform selection, always balancing scalability, risk, and total cost of ownership. 

Build and lead a multi-disciplinary engineering organisation spanning software, ML, data, and platform engineering, attracting and developing exceptional talent while creating clear career paths for senior technical leaders. Set engineering culture and standards for code quality, testing, documentation, peer review, and production readiness so that solutions are robust from prototype through to long-term operation. Shape team topology and investment allocation across discovery, delivery, and sustainment to ensure capacity is focused on the highest-impact opportunities. 

Own end-to-end engineering delivery from architecture through to production deployment, scaling, monitoring, and lifecycle management. Partner with EAIT to leverage enterprise platforms, infrastructure, and shared services so that Enabling Function solutions are built on common foundations and contribute back to enterprise capability. Establish standards for model serving, data pipelines, APIs, integration patterns, security, observability, and MLOps practices including CI/CD, automated testing, performance monitoring, incident management, and capacity planning. Ensure rapid experimentation with clear gates between prototype, pilot, and production so that innovation moves quickly without compromising quality. 

Drive scaling through partnership as a defining feature of the role. Orchestrate delivery across EAIT shared services, functional teams in Legal, Procurement, Finance, Audit and Compliance, and external technology partners to multiply impact without linear headcount growth. Identify where solutions proven in one domain can be adapted to others – for example reusing document intelligence capabilities from Legal in Procurement or Audit – and build a scaling model that embeds reuse by design. Shape joint programmes with external partners, defining technical scope, integration architecture, IP boundaries, and quality standards to ensure outcomes are production-grade rather than isolated proofs-of-concept. 

Own the data engineering strategy for AI across Enabling Functions. Define pipelines, feature stores, and data products designed for quality, governance, lineage, and reuse across SOX-relevant financial data, legally privileged documents, and PII subject to GDPR/HIPAA. Drive integration architecture with core enterprise platforms such as ERP systems, CLM tools, procurement platforms and GRC solutions without creating ungoverned data stores or fragile dependencies. Embed governance-by-design into engineering practices through model registration, data/model cards, performance monitoring frameworks and human-in-the-loop oversight. 

Ensure compliance with EU AI Act requirements as they evolve, GDPR, HIPAA, SOX and legal privilege protections by building responsible AI capabilities at scale – including automated fairness testing, explainability pipelines and decision audit trails embedded into standard workflows. Own technical risk management across the portfolio covering model degradation, data quality issues, dependency risk and integration risk. Act as a senior technical partner to C-suite stakeholders across Enabling Functions, translating engineering complexity into business language so leaders can make informed investment decisions. 

Represent Enabling Functions within the enterprise AI engineering organisation and EAIT leadership forums. Contribute to enterprise governance including architecture review boards and standards evolution. Drive reuse and knowledge sharing by identifying where patterns developed for Enabling Functions can accelerate delivery elsewhere in the company – and where enterprise patterns can be applied back into finance, legal or compliance contexts. Advocate for the specific needs of regulated, process-critical functions within broader platform roadmaps so that enterprise AI capabilities are fit for purpose in these demanding environments.

Essential Skills/Experience 

Leadership 

• Significant experience in engineering roles, with some of this experience being at Director level or above leading organisations of 50+ engineers 

• Proven production-scale AI/ML delivery in complex, cross-functional environments — not just prototypes 

• Track record of scaling through partnership — orchestrating across internal platform teams, business functions, and external partners 

Technical 

• Deep architectural expertise across the AI/ML stack — model development, MLOps, data engineering, cloud infrastructure, and integration design 

• Authoritative judgement on build-vs-buy, model strategy (foundation models, fine-tuning, RAG), and platform selection 

• Strong software engineering standards — CI/CD, testing, observability, production operations 

Domain and Governance 

• Delivery within regulated environments where auditability, data sensitivity, and compliance are non-negotiable 

• Practical AI governance experience — model validation, bias detection, explainability, monitoring, human-in-the-loop design 

• Working knowledge of GDPR and at least one of SOX, EU AI Act, or equivalent regulatory frameworks 

Stakeholder 

• Credible C-suite partnership — ability to translate engineering complexity into business language and influence investment decisions 

• Experience balancing competing priorities across multiple business functions with architectural coherence 

Education 

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related discipline (or equivalent experience) 

Desirable Skills/Experience 

Domain 

• Direct experience delivering AI/technology into Legal, Procurement, Finance, Audit, or Compliance 

• Familiarity with enterprise platforms relevant to Enabling Functions (SAP, Oracle, Coupa, CLM, GRC tools) 

• Understanding of pharmaceutical industry context and AI adoption dynamics in life sciences 

Technical 

• Experience with document intelligence, NLP, and LLM deployment at enterprise scale (fine-tuning, RAG, guardrails) 

• Background in data platform engineering — feature stores, data products, real-time and batch pipelines 

• Hands-on experience with MLOps platforms (MLflow, Kubeflow, SageMaker, Vertex AI, or equivalent) 

Leadership 

• Experience building engineering capability from the ground up — recruiting, structuring, and scaling through rapid growth 

• Track record in matrixed organisations where delivery depends on influencing beyond direct reporting lines 

• Success driving AI adoption in risk-averse, compliance-driven cultures 

• Strategic vendor and partner management including co-development, technical due diligence, and integration governance 

Education 

• Advanced degree (MSc, PhD) in Computer Science, Machine Learning, AI, or related field 

• Relevant cloud, AI/ML, or enterprise architecture certifications (AWS/Azure/GCP Professional, TOGAF) 

When we put unexpected teams in the same room, we unleash bold thinking with the power to

inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge

perceptions. That's why we work, on average, a minimum of three days per week from the office. But that

doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual

flexibility. Join us in our unique and ambitious world.

AstraZeneca offers an environment where technology leaders can disrupt an industry while seeing direct impact on patients’ lives; work spans cutting-edge AI and data platforms through to real-world applications that transform how medicines are discovered, developed and delivered. Teams are empowered to experiment with modern tools and architectures in a fast-moving yet disciplined setting – from hackathons to large-scale programmes – supported by strong investment in digital capabilities. Collaboration with diverse experts across science and technology opens up constant opportunities to learn new domains while deepening technical mastery. Continuous development is central: recognition, coaching and feedback underpin a culture where curiosity is encouraged every day and career paths can evolve in many directions as technologies change.

If this role matches your experience and ambition to lead AI engineering at scale in a highly impactful setting, please apply now.

#EAI

Date Posted

04-May-2026

Closing Date

18-May-2026

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.