Head of Artificial Intelligence – ICC

Head of Artificial Intelligence ICC

Are you ready to build and lead a high-impact AI organization that turns sophisticated biology into decisive action for patients Can you unite distributed expertise into a single strategic engine that accelerates discovery and transforms how we work end to end

AstraZeneca is creating a new leadership role to consolidate and direct AI across Cell Therapy Discovery and Targeted Immune Engagers. Based in the United States (GTB or BOS) the United Kingdom (Cambridge) or the Netherlands (Amsterdam) you will compose the AI strategy lead delivery of a high-value portfolio and embed AI as a core capability powering our next wave of medicines. As a member of the CTD and TIE leadership teams reporting to the SVP for IO Discovery and Cell Therapy Oncology you will set direction mobilize talent and deliver measurable impact across discovery and operations.

This is a hands-on build-and-scale mandate. You will form a centralized group of AI experts embedded with R&D teams orchestrate initiatives from agentic knowledge hubs to predictive CAR-T models and in silico binder design and establish the governance and operating rhythm that turns prototypes into durable platforms and outcomes.

Accountabilities:

- Strategic Leadership: Define and implement the end-to-end AI strategy across CTD and TIE aligned to enterprise AI goals with a clear roadmap for and beyond.
- Portfolio Orchestration: Prioritize and deliver a focused slate of initiatives including agentic knowledge hubs predictive modeling for cell therapy in silico protein and binder design TCR affinity maturation CRISPR off-target safety and next-generation analytics.
- Agentic AI Development: Build test and scale knowledge hub capabilities that enable collaborative analysis rapid retrieval of institutional knowledge and faster better decisions.
- Predictive Modeling for Cell Therapy: Lead models that optimize CAR-T design and performance reducing cycle times from hypothesis to validation and improving program selection.
- In Silico Protein and Binder Design: Deploy AI workflows that generate and refine binders and mature affinity increasing hit quality and reducing experimental burden.
- CRISPR Safety and Risk: Implement sophisticated off-target workflows to improve safety assessments strengthen study build and de-risk pipelines.
- Workflow Automation: Automate research and analytics processes to streamline operations reduce manual effort and increase reproducibility across sites and teams.
- AI Upskilling and Culture: Orchestrate training that lifts foundational AI literacy and fosters an innovative high-integrity culture where scientists and engineers co-create solutions.
- Collaborator Partnership: Build deep collaboration with enterprise AI platform and external partners to align standards share knowledge and improve resource leverage.
- Governance and Value Realization: Implement robust governance regulatory compliance and budget/resource management; institute KPIs that quantify scientific and operational value.
- Communication and Influence: Translate sophisticated technical insights into clear narratives for executive and non-technical collaborators shaping R&D strategy and investment decisions.

Essential Skills/Experience:

- Advanced degree (Masters or PhD) in Computer Science Engineering Mathematics or a related quantitative field.
- Demonstrated 10 years of experience successfully leading high-performing AI teams and sophisticated AI programs ideally in life sciences technology or R&D-driven environments.
- Strategic skill in shaping scaling and transforming AI activities for maximum business and scientific impact.
- Expertise in the development and deployment of AI/ML technologies with proven outcomes in sophisticated multi-stakeholder environments.
- Strong understanding of biology or R&D workflows preferred but not required; ability to translate between technical and scientific teams is essential.
- Outstanding organizational communication and collaborator engagement skills including experience communicating/translating sophisticated technical findings and priorities to executive and non-technical partners.
- Proven experience building mentoring and scaling multi-disciplinary teams comprised of machine learning scientists AI engineers and data professionals distributed across multiple locations and embedded in different R&D teams.
- Track record of encouraging a collaborative innovative and high-integrity team culture.

Desirable Skills/Experience:

- Direct experience applying AI/ML to cell therapy protein engineering immunology or related modalities.
- Demonstrated delivery of one or more: agentic knowledge hubs CAR-T predictive models in silico binder generation TCR affinity maturation workflows CRISPR off-target analyses or computational mutagenesis.
- Familiarity with LLMs knowledge graphs MLOps and cloud-native platforms; experience integrating these into enterprise environments.
- Experience with data governance model risk management and compliance practices relevant to R&D and regulated settings.
- Success managing multi-site teams and external ecosystems including vendors consortia and academic collaborations.
- Portfolio management experience with clear KPI frameworks and budget ownership.

When we put unexpected teams in the same room we unleash ambitious thinking with the power to encourage life-changing -person working gives us the platform we need to connect work at pace and challenge perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our outstanding and ambitious world!

Why AstraZeneca:

Here ground breaking science meets ambitious technology in service of patients. You will join a community that thrives on collaboration across subject areas where ideas move quickly from exploration to scaled platforms that change how we discover and develop medicines. We put unexpected teams together to unlock new thinking invest deeply in digital capabilities across the R&D lifecycle and value kindness alongside ambition so people can take smart risks and learn fast. Your leadership will connect AI breakthroughs to tangible outcomes for patients and programs while opening new horizons for your own growth.

Date Posted

Closing Date

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