AstraZeneca
AITechnicalBusinessPartner,Director–R&DChina
Neural analysis suggests this role is
optimal for Director candidates.
“AI Technical Business Partner, Director – R&D China at AstraZeneca. Skills: Scaling AI/ML products, AI strategy, Data engineering for AI, Solution architecture, Agent orchestration, Governance and technical risk, Cross-functional leadership, Strategic communication. Lead the industrialization of AI across R&D organization. Define the AI-ready data strategy”
What You'll Achieve.
Operationalize intelligence at scale; Transition AI from 'experimental notebooks' to 'enterprise capabilities'; Ensure data foundation is AI-ready; Ensure technical architecture is secure, compliant, and integrated; Scale AI/ML products from concept to enterprise-wide deployment; Define the corporate AI infrastructure for the next decade of drug discovery
Industry & Context.
Feasibility Analysis; Technical Discovery; Solution Architecture; Governance & Technical Risk
What They're Looking For.
Must Have
Scaling AI/ML products from concept to enterprise-wide deployment, Experience with MLOps best practices, Deep understanding of data engineering for AI, Experience designing Feature Stores or Knowledge Graphs, Experience working with sensitive healthcare data (PII/PHI), Understanding of Human Genetic Resources (HGR) regulations, Grasp of cloud architectures (AWS/Tencent/Ali), Understanding of containerization (Docker/Kubernetes), Experience with enterprise AI platforms, Experience with vector database architectures, Proficiency in Python for data analysis and prototyping, Ability to drive consensus across stakeholders, Ability to explain technical concepts to C-suite
Nice to Have
Familiarity with scientific data standards (HL7, FHIR, CDISC), Experience with MLflow, Kubeflow, model registry, Experience with Databricks, Snowflake, Experience with specific ML frameworks (Llama-3, BioMistral), Experience with low-code orchestration platforms, Experience with Model Context Protocol (MCP), Experience with scientific software integration (Schrödinger Maestro, Benchling), Experience with GxP and 21 CFR Part 11 standards, Experience with automated evaluation frameworks (LLM-as-a-Judge), Experience with prompt injection attacks, Experience with cloud platforms (AWS/Tencent/Ali), Experience with containerization (Docker/Kubernetes)
What You'll Do.
Lead the industrialization of AI across R&D organization
Define the AI-ready data strategy
Partner with data and AI Infrastructure teams
Ensure AI solutions transition from pilots to corporate assets
Build Proof-of-Concepts (PoCs)
Evaluate feasibility of AI requests
Manage local AI environments
Design agentic workflows
Act as Data Engineering Liaison
Map technical integration of AI tools
Red Team internal models
Implement security guardrails
Ensure compliance with GxP and 21 CFR Part 11 standards
How You'll Work.
Team & Collaboration
Partner deeply with our data and AI Infrastructure teams; Drive consensus across stakeholders (Scientists, Engineers, Security/Legal)
Communication Scope
Strategic communication; Ability to explain to the C-suite why 'cleaning data' is a capital investment required for 'AI success'
Full Job Description
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 senior **AI Technical Business Partner** to lead the industrialization of AI across our R&D organization. This is not just a prototyping role; it is a scaling role. You will bridge the gap between scientific intent and enterprise-grade software execution. You will define the **AI-ready data strategy** , partner deeply with our **data** and **AI Infrastructure** teams, and ensure that our AI solutions transition from isolated pilots to robust, secure, and scalable corporate assets. **Mission** To operationalize intelligence at scale. You will drive the transition of AI from "experimental notebooks" to "enterprise capabilities," ensuring that our data foundation is AI-ready and our technical architecture is secure, compliant, and integrated with the global ecosystem. **Key Responsibilities** **1\. Technical Discovery & Rapid Prototyping (The "Builder")** * **Build Proof-of-Concepts (PoCs):** Don't just write a requirements doc; build the MVP. Use Python, LangChain, or low-code orchestration platforms to spin up functional prototypes (e.g., a RAG-based literature review bot or a molecule property predictor) to validate use cases with scientists immediately. * **Feasibility Analysis:** Evaluate incoming requests not just for business value, but for technical reality. Assess data readiness, API availability, and model suitability (e.g., "Can Llama-3 handle this toxicology reasoning, or do we need a fine-tuned BioMistral model?"). * **Sandbox Management:** Manage local AI environments for your therapeutic area, ensuring scientists have secure, compliant access to te
Applying for this AI Technical Business Partner, Director – R&D China role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about AstraZeneca?
Real rants from real employees. Read before you apply.