About the Beijing AI Center
The Beijing AI Center is a new strategic investment by AstraZeneca to accelerate drug discovery through AI. The center brings together AI researchers, computational scientists, and platform engineers to apply foundation models, agentic AI, and large-scale scientific computing to real R&D problems. Situated in one of the world’s most dynamic AI talent markets, it operates at the intersection of biologics discovery, computational chemistry, and AI-driven drug discovery.
The center is structured around three pillars: Discovery verticals (therapeutic design and preclinical predictions), Data & AI Platforms, and Ecosystem Partnerships with leading Chinese academic institutions and AI companies. This role sits within the Data & AI Platforms pillar, with a mandate to bring the center’s Agentic AI platform to life for China R&D.
About the Role
This role owns the Agentic AI platform for AstraZeneca’s China R&D organization. You are the single point of product accountability — from vision and roadmap through delivery and measured impact — for the platform that puts agentic AI capabilities in the hands of China R&D scientists and functions.
You connect demand to delivery. You partner with internal customers across China R&D to identify and frame the problems worth solving, translate them into a compelling product vision and a prioritized roadmap, and work with engineers, scientists, and platform teams to ship the right capabilities. You use data and evidence — not opinion — to drive prioritization and trade-off decisions, escalating when necessary without damaging relationships.
You operate at the seams of the organization. The platform only delivers value when it is wired into the broader ecosystem, so you will interface continuously with China R&D, Business Development (BD), and global functions including Enterprise AI — ensuring the China platform both leverages and contributes to AstraZeneca’s enterprise-wide AI strategy.
You will be most visible where the work is hardest. You will own the entire product lifecycle, represent the platform independently across organizations and technical levels, and personally drive the most ambiguous, cross-functional, or time-sensitive decisions from concept through production.
What You Will Do
Product Vision & Roadmap (35%)
- Connect with internal customers across China R&D to identify, frame, and prioritize the problems the Agentic AI platform will solve
- Create a compelling product vision and strategy for the Agentic AI platform that solves complex R&D business problems and aligns to China R&D and enterprise priorities
- Own the product roadmap and blueprint — sequencing capabilities to ensure value delivery through well-scoped MVPs and prioritized use cases
- Manage trade-off decisions between business opportunities and available resources, using data and evidence to drive prioritization
- Assess build, buy, and partner options for platform capabilities, evaluating partnership and technology opportunities for strategic fit and feasibility
Execution & Delivery (40%)
- Own the entire product lifecycle of the Agentic AI platform, working with engineers, scientists, and other stakeholders to deliver the right products
- Drive execution, implementation, and delivery of prioritized use cases from idea to production, following lean and agile principles
- Translate requirements into delivery through clear requirements engineering, backlog ownership, and scrum-based ways of working
- Measure and communicate impact — define success metrics for the platform and its use cases, instrument them, and use the results to refine the roadmap
- Explore and solicit innovative concepts and technologies with stakeholders, incorporating emerging agentic AI capabilities into the platform
Stakeholder Engagement & Communication (25%)
- Interface across China R&D, BD, and global functions including Enterprise AI — ensuring the China platform aligns with and contributes to AstraZeneca’s enterprise AI strategy
- Independently represent the platform and the team, communicating comfortably across organizations and at varying technical levels
- Escalate when necessary to unblock delivery and reconcile business strategy with technical needs, without damaging relationships
- Evangelize the platform’s capabilities and accomplishments through targeted communications, celebration of achievements, and internal and external forums
Requirements
Experience
- 8+ years in science-based technical product management, or equivalent experience in AI/ML development
- Track record of developing strategic product ideas and plans, building technical proposals, and delivering product visions
- Demonstrated ability to drive an AI-based solution from idea to production
- Experience working in cross-functional or matrix environments, influencing across stakeholders
Skills
- Good understanding of ML/AI/DL techniques, preferably with hands-on experience
- Ability to manage trade-off decisions between business opportunities and available resources
- Strong requirements engineering following lean and agile principles, with experience in scrum
- Highly collaborative, with strong stakeholder communication and management across technical and non-technical audiences
- Able to translate across communication gaps around highly technical information and lead diverse teams toward a common goal
- Understanding of R&D, data science and AI, informatics, records management, and system development in the biotech/pharma industry
China-Specific
- Ability to work in Shanghai or Beijing on-site
- Mandarin fluency required
- Experience with data and AI regulations in China (e.g., PIPL, DSL, and cross-border data transfer requirements) is highly desirable
- Familiarity with the Beijing talent and innovation ecosystem is an advantage
Mindset
- Comfortable with ambiguity: the center and the platform are still being built and priorities will evolve
- Bias to ownership: takes end-to-end accountability for the product and drives it without prompting
- Passion for learning new technologies and applying them to real scientific problems
- Energized by leading and influencing across functions to deliver shared outcomes
Nice-to-Have
- Experience applying AI technologies to scientific or consumer products from idea to production
- Experience with AI data preparation techniques in bioinformatics, ML frameworks, and tooling
- Knowledge of (immune) oncology and drug development processes
- Clinical, diagnostic, or translational science operations experience
- Experience driving innovation events (e.g., hackathons) toward novel solutions
Date Posted
29-9月-2026Closing Date
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.
Skills Required
- 8+ years of experience in science-based technical product management or equivalent AI/ML development experience
- Experience developing strategic product ideas and plans, technical proposals, and product visions
- Demonstrated ability to drive an AI-based solution from concept to production
- Experience working in cross-functional or matrix environments and influencing stakeholders
- Strong understanding of machine learning, artificial intelligence, and deep learning techniques
- Ability to manage trade-off decisions between business opportunities and available resources
- Requirements engineering experience using lean, agile, and Scrum methodologies
- Strong stakeholder communication and management skills across technical and non-technical audiences
- Ability to translate highly technical information and lead diverse teams toward common goals
- Understanding of R&D, data science, AI, informatics, records management, and systems development in the biotech or pharmaceutical industry
- Ability to work on-site in Beijing or Shanghai
- Mandarin fluency
- Experience with China data and AI regulations, including PIPL, DSL, and cross-border data transfer requirements
- Familiarity with the Beijing talent and innovation ecosystem
- Experience applying AI technologies to scientific or consumer products from concept to production
- Experience with AI data preparation techniques, bioinformatics, ML frameworks, and tooling
- Knowledge of immune oncology and drug development processes
- Clinical, diagnostic, or translational science operations experience
- Experience driving innovation events such as hackathons toward novel solutions
AstraZeneca Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AstraZeneca and has not been reviewed or approved by AstraZeneca.
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Fair & Transparent Compensation — Pay is considered competitive across many roles when total rewards are factored in. Senior scientific and leadership bands are described with high ranges that reinforce competitiveness at upper levels.
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Strong & Reliable Incentives — Bonuses, equity eligibility in many salaried roles, and solid sales on‑target earnings with upside are emphasized as meaningful parts of compensation. These elements boost overall value even where base pay is not the very highest.
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Retirement Support — A 401(k) program with a strong company match and immediate vesting is repeatedly cited as a standout. Generous retirement support is viewed as enhancing the total package relative to peers.
AstraZeneca Insights
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