Associate Director of Generative AI

Introduction to role

Predictive AI and Data team is responsible for providing AI and Bioinformatics solutions to the scientists across the spectrum of drug development and discovery in AstraZeneca (both pre-clinical and clinical stages). The primary aim is to find ways to accelerate the drug development process by leveraging existing company data in combination with the most cutting-edge AI approaches as well as implement agentic workflows and foundation models in day-to-day scientific work across the company.

This role is similar to a forward deployed engineer (FDE) and will work directly with customers across the spectrum of drug development pipeline to configure and implement generative AI solutions (including Large Language Models, other Foundation Models and Agentic AI workflows) to demonstrate value to the business in accelerating existing scientific processes. You will then help build out the robust solution in production in collaboration with other data science and software developer teams.

Accountabilities

- Collaborate with scientists from across the company to understand their challenges and work with them to build the platform that underpins their research.
- Build generative AI prototype solutions to demonstrate value in accelerating routine scientific processes.
- Calculate ROI and impact for AI projects obtaining necessary information and assumptions from stakeholders and future users.
- Provide strategic direction and leadership for the organisation as well as collaborate with senior leadership to define and implement the generative AI strategy, finding opportunities for generative AI adoption and driving business impact.
- Champion a “production first attitude” to ensure the necessary infrastructure and platforms are available to scale exploratory research to production.
- Be a part of a hard-working team, continuously improving AstraZeneca’s Machine Learning development environments, platforms, and tooling.
- Work closely and collaboratively with internal governance and compliance functions such as Cyber Security and Data Privacy to secure the computing environment without obstructing end-user productivity.

Essential Skills/Experience

- Bachelor’s degree, or Master’s (or equivalent years of experience) in mathematics, computer science, engineering, physics, statistics, computational sciences or a related field.
- Advanced skills in programming languages such as Python, and experience with AI libraries and frameworks (e.g., TensorFlow, PyTorch).
- Proven experience in AI and machine learning, in areas such as deep learning, natural language processing, computer vision, and reinforcement learning.
- Experience in prompt engineering, implementing Retrieval-Augmented Generation (RAG), and LLM fine-tuning.
- Demonstrated experience in implementing generative AI workflows (large language models, other foundation models or agentic frameworks) to automate existing process or enable new ones, ideally in the Pharma and/or Healthcare space.
- Experience designing agentic AI workflows and an ability to plan strategically for the AI needs in a large organisation.
- Strong knowledge of software development and machine learning deployment principles.
- Demonstratable experience working with AWS or a similar cloud environment.
- Experience working with Kubernetes and/or container-based application deployments.
- Excellent communication and presentation skills, with the ability to convey complex AI concepts to non-technical partners.
- Strong leadership and project management skills, with a track record of leading successful AI projects.
- Knowledge of AI ethics and responsible AI practices.

Desirable Skills/Experience 

- Experience in life sciences, healthcare, or pharmaceutical industry.
- Experience in a complex global organization.
- Experience using DevOps and MLOps to enable automation strategies.
- Experience with LLM frameworks (LangChain, AutoGen, LlamaIndex).
- Experience working in an Agile team with knowledge or experience of working in product or platform-focused delivery.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

AstraZeneca offers an inspiring environment where you can thrive alongside a community of highly qualified scientists. We continuously share knowledge, constructively critique our work, and push each other towards groundbreaking solutions. Our dedication to improving patient outcomes drives us forward every day.

Ready to make a difference? Apply now!

Date Posted

Closing 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.