AstraZeneca
From AstraZeneca's careers page
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A. Cloud Architecture, Cloud Operations Management & AI Enablement
Own the target architecture and technology roadmap for China cloud platforms across Alibaba Cloud and AWS, translating global enterprise architecture, technology standards, and security policies into China-ready architectures that meet local regulatory and operational requirements.
Define and manage the cloud landing zone, including account structures, network connectivity, identity and access management, security baselines, observability, and infrastructure automation, and establish reusable reference architectures, design patterns, and technical guardrails.
Define cloud operations standards and governance covering monitoring, incident, problem, and change management, backup and recovery, vulnerability remediation, capacity management, service continuity, and regular service health and operational risk reviews.
Partner with security and compliance teams to translate policies, control frameworks, and risk requirements into practical architecture standards, technical designs, operational procedures, and audit evidence.
Lead the roadmap for AI-enabled cloud governance and operations, prioritizing high-value use cases (e.g., automated incident analysis, configuration validation, compliance checks, cost optimization, and self-healing), promoting Infrastructure as Code, policy as code, and AI-assisted engineering, and tracking measurable outcomes such as automation coverage and reduction of manual effort.
B. MaaS Solution Engineering & Operations Management
Own the architecture, solution engineering, and operational roadmap for enterprise MaaS capabilities, including model access, integration, serving, inference, routing, AI engines, and shared AI services, translating business, application, and compliance requirements into standardized, scalable, and secure solutions.
Design and engineer reusable MaaS solution patterns and model-serving capabilities across Alibaba Cloud, AWS, and local infrastructure, covering model onboarding and evaluation, API integration, authentication and authorization, traffic and quota management, usage metering, and monitoring, while balancing performance, GPU availability, data residency, and cost.
Manage the end-to-end MaaS service lifecycle, from demand assessment and solution design through production readiness, operations, version upgrades, and retirement, with defined service levels, capacity requirements, support procedures, and escalation paths.
Enable application teams with standardized model and agent services through reusable APIs, templates, self-service capabilities, documentation, and runbooks, embedding security and data protection controls such as model access controls, sensitive data handling, agent permissions, and auditability.
Lead MaaS incident and problem management, and drive continuous optimization of performance, capacity, model selection, token consumption, and cost (FinOps), while evaluating emerging AI technologies to inform platform evolution and investment decisions.
C. Cloud-Native Solutions, Platform Engineering & Operations Management
Provide cloud architecture, cloud-native solution design, and platform services for web applications, data and BI platforms, AI workloads, integration services, and shared technology capabilities across Alibaba Cloud and AWS.
Establish engineering standards, reusable platform components, blueprints, and deployment templates for infrastructure provisioning, configuration management, deployment automation, observability, backup, and disaster recovery.
Define and manage the operational lifecycle of cloud-native platforms, including reliability, availability, performance, and capacity requirements, production readiness criteria, and operational procedures for access management, patching, vulnerability remediation, and certificate and secret management.
Lead incident response, root cause analysis, and problem management for cloud-native platforms, and support security teams in implementing and operating security controls across infrastructure, workloads, identities, networks, and logging.
Continuously improve platform services based on operational insights, incident trends, security findings, application team feedback, and AI-assisted analysis.
D. Platform Service Ownership & Delivery
Define the platform service catalogue, service boundaries, technical ownership, service levels, support model, and consumption model for cloud infrastructure, AI/MaaS, BI, and shared platform capabilities.
Act as the technical interface between platform engineering, platform operations, security, and application delivery teams, translating business, operational, and control requirements into standardized platform services.
Establish service onboarding, technical design review, production readiness, service transition, and change management processes, promoting self-service provisioning, reusable templates, and AI-assisted support to improve application team autonomy and secure-by-design adoption.
Collaborate with IT leadership, project teams, security and compliance stakeholders, vendors, and Global stakeholders to prioritize platform initiatives, manage dependencies, and assess delivery and operational risks.
Ensure platform services provide the technical evidence, logging, and control records needed for security reviews and audits, and conduct regular service reviews covering availability, incidents, capacity, performance, cost, and user satisfaction.
E. Cloud Economics & Engineering Excellence
Establish cloud and AI platform cost governance, including cost allocation, showback, consumption visibility, budget monitoring, and optimization of resource utilization and model-serving efficiency.
Evaluate architecture, engineering, and operational trade-offs across Alibaba Cloud, AWS, AI infrastructure, and managed services to balance cost, reliability, security, and supportability.
Define engineering, service management, and operational KPIs to measure platform reliability, delivery efficiency, automation maturity, AI-enabled productivity, service quality, and cost effectiveness.
Develop a continuous improvement roadmap that balances operational stability with long-term platform modernization, service management maturity, and Agentic AI adoption.
Promote repeatable, auditable, and AI-assisted engineering and operations practices, supported by knowledge management, documentation, runbooks, and training.
JOB REQUIREMENTS & COMPETENCIES
Job requirements / 工 作 要 求
Bachelor’s degree or above in Computer Science, Software Engineering, Information Technology, or a related technical discipline; Master’s degree preferred.
Professional cloud architecture certifications preferred, such as Alibaba Cloud ACE/ACP, AWS Certified Solutions Architect – Professional, or AWS Certified DevOps Engineer – Professional; ITIL, TOGAF, Kubernetes (CKA/CKS), or FinOps certifications are a plus.
In-depth knowledge of cloud architecture across Alibaba Cloud and AWS, including landing zones, networking, identity and access management, security baselines, observability, and infrastructure automation (Infrastructure as Code and policy as code).
Solid understanding of AI platform and MaaS technologies, including model serving, inference frameworks, model gateways and routing, GPU capacity management, LLM application patterns, and Agentic AI runtimes and tooling.
Strong grounding in IT service management and cloud operations practices, including incident, problem, and change management, SRE principles, disaster recovery, capacity planning, and FinOps.
Working experience (No. of years / 年 资, Job function / 工 作 功 能, Business types / 业 务 种 类 ):
10+ years of experience in IT infrastructure, cloud engineering, or platform engineering, including at least 5 years in cloud architecture or platform leadership roles in large enterprise environments.
Proven experience designing, implementing, and operating enterprise cloud platforms on Alibaba Cloud and/or AWS in China, with a solid understanding of China-specific regulatory, data residency, and cybersecurity requirements.
Demonstrated track record of owning platform services end-to-end, from architecture and implementation through production operations, service levels, incident management, and continuous improvement.
Experience leading and developing engineering and operations teams, and managing vendors and strategic technology partners.
Hands-on experience building or operating enterprise MaaS, model-serving, or AI platform capabilities, and enabling AI agents in production at scale.
Experience applying AI to cloud governance and operations (AIOps), such as automated incident analysis, configuration validation, compliance checks, and self-healing.
Experience in a regulated industry (e.g., pharmaceutical or life sciences), including GxP, data integrity, and audit readiness requirements, and in working within a global matrix organization.
Fluent in English and Mandarin Chinese, with the ability to communicate effectively with Global and local stakeholders, present to senior leadership, and produce high-quality technical and management documentation.
Strategic thinker with strong technical depth, able to translate business objectives and global standards into practical, locally compliant platform roadmaps.
Strong leadership, stakeholder management, and influencing skills across IT leadership, application, security, compliance, operations, and vendor teams.
Results-oriented, with strong ownership, sound judgment in balancing innovation, risk, cost, and operational stability, and a commitment to continuous learning in cloud and AI technologies.
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.
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