Lead of AI Infrastructure Platform

At AstraZeneca we’re dedicated to being a Great Place to Work. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. We’re focused on the potential of science to address the
unmet needs of patients around the world. We commit to those areas where we think we can really change the course of medicine and bring new ideas to life.

Summary

We are seeking a high-caliber Lead of AI Infrastructure Platform to architect and operate the foundation for our AI-driven R&D. In 2026, AI infrastructure is no longer just about racking GPUs; it is about building a "Compound AI System" that is resilient, sovereign, and cost-optimized.

You will lead an elite team to transform raw compute into a strategic asset, moving from Proof-of-Concept to Proof-of-Impact. You will be the primary authority on our AI hardware-software co-design, ensuring our R&D teams can train, fine-tune, and deploy frontier models at unprecedented scale and efficiency.

Key Responsibilities

1. Visionary Architecture & "AI Factory" Operations

• Next-Gen Orchestration: Design and manage a unified execution environment (CPUs, GPUs, and AI ASICs) using modern orchestration layers that support both training and low-latency inference.

• LLMOps & Agentic Infrastructure: Implement robust pipelines for LLMOps, specifically focusing on prompt versioning, vector database scaling, and the infrastructure required to host autonomous AI Agents.

• Sovereignty & Compliance: Navigate the complex Chinese AI landscape to ensure infrastructure compliance with local data residency and security regulations, while maintaining performance.

2. Strategic Technology Leadership

• Performance Engineering: Lead deep-dive optimizations in distributed training (DeepSpeed, Megatron) and hardware-aware model tuning to extract maximum TFLOPS from every cluster.

• Sustainability & Green AI: Implement carbon-aware scheduling and liquid-cooling strategies to reduce the environmental footprint and operational costs of high-density workloads.

• Vendor Strategy: Manage a diverse portfolio of domestic and international hardware/cloud vendors, ensuring a resilient supply chain in a volatile hardware market.

3. Cross-Functional Execution

• Stakeholder Alignment: Translate complex R&D ambitions into technical infrastructure requirements, acting as the bridge between researchers and the IT finance office.

• Talent Incubation: Build and mentor a "Full-Stack" infrastructure team capable of handling everything from high-speed InfiniBand networking to Kubernetes-based model serving.

Qualifications & Requirements

• Experience: 10+ years in Infrastructure/Systems Engineering, with 4+ years specifically leading AI-focused platforms.

• Technical Mastery:

  • Expertise in GPU cluster management (e.g., NVIDIA Blackwell/H-series or domestic equivalents) and high-performance interconnects (RoCE v2, InfiniBand).

  • Deep knowledge of the Chinese AI Landscape, including Aliyun/Huawei Cloud/Baidu and local hardware ecosystems.

  • Hands-on experience with FinOps for AI, specifically managing the "Inference Economics" of large-scale model deployment.

• Software Stack: Proficiency in PyTorch, Ray, Kubernetes (KubeFlow), and modern observability tools (Prometheus/Grafana) for real-time hardware telemetry.

• Mindset: A "Systems Architect" approach—viewing the entire data center as a single programmable computer.

Date Posted

05-6月-2026

Closing Date

07-6月-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.