Job Title: Associate Director of Software Engineering - Scientific & AI Tools
Introduction to role:
Are you ready to turn cutting-edge science into scalable software that speeds breakthroughs to patients In this role you will lead the engineering of scientific and AI tools that empower researchers to ask better questions make faster decisions and unlock insights from complex data. Your work will bridge advanced computation with real-world discovery enabling our scientists to move promising assets forward with confidence.
You will guide a multi-disciplinary team to fuse modern software engineering large language models and robust data platforms into products that scientists love and trust. How will you translate messy real-world scientific needs into elegant reliable systems that raise the bar for productivity and rigor If you thrive at the intersection of science AI and engineering craftsmanship this is where your impact scales.
Accountabilities:
- Product Leadership: Own the end-to-end delivery of fit-for-purpose tools translating scientific and business needs into clear technical roadmaps that deliver measurable value for researchers and program teams.
- Architecture and Development: Design build and operate scalable software across scientific data and AI domains applying modern engineering practices to ensure resilience security and maintainability.
- AI Solutions: Implement Large Language Modelpowered systems Retrieval-Augmented Generation (RAG) and agentic workflows that accelerate scientific workflows and help experts focus on high-value decisions.
- Data Platforms: Build and evolve data ingestion transformation and visualization solutions; enforce data quality security lineage and governance to create trustworthy discoverable assets.
- Collaboration: Partner with CPSS stakeholders R&D IT and DS&AI to co-create solutions; communicate complex topics clearly to diverse audiences and drive alignment across research and technology.
- Operational Excellence: Establish CI/CD automated testing observability and DevOps practices; ensure reliability performance and cost efficiency in cloud and HPC environments.
- Technical Mentorship: Guide engineers and contributors; foster a culture of craftsmanship learning and inclusive collaboration that raises standards across teams and projects.
Essential Skills/Experience:
- Product leadership: Translate scientific and business requirements into technical roadmaps; own delivery of fit-for-purpose tools end-to-end.
- Architecture and development: Compose build and operate scalable software in scientific data and AI domains applying modern engineering guidelines.
- AI solutions: Implement Large Language Modelpowered systems Retrieval-Augmented Generation (RAG) and agentic workflows to enhance scientist productivity.
- Data platforms: Build data ingestion transformation and visualization solutions; ensure data quality security lineage and governance.
- Collaboration: Work closely alongside CPSS contacts R&D IT and DS&AI to co-create solutions; provide clear communication of complex topics to diverse audiences.
- Operational excellence: Establish CI/CD automated testing observability and DevOps practices; ensure reliability performance and cost efficiency in cloud and HPC environments.
- Technical mentorship: Guide engineers and contributors; foster a culture of craftsmanship learning and inclusive collaboration.
Desirable Skills/Experience:
- Hands-on experience with cloud platforms (Azure AWS or GCP) and HPC schedulers (e.g. Slurm) including cost-aware architecture design.
- Proficiency in Python and one or more of TypeScript/Java; familiarity with microservices event-driven architectures and APIs.
- Experience with containerization and orchestration (Docker Kubernetes) and infrastructure-as-code (Terraform CloudFormation).
- Applied LLM tooling and frameworks (e.g. LangChain Semantic Kernel) vector databases and embeddings and prompt/agent design at production scale.
- Strong data platform engineering: streaming and batch pipelines data modeling lineage catalogs and visualization; experience with knowledge graphs and search.
- Robust CI/CD and observability using GitHub Actions/Azure DevOps openTelemetry Prometheus Grafana and modern testing practices.
- Background in scientific computing bioinformatics or cheminformatics and familiarity with FAIR data principles and secure-by-design patterns.
When we put unexpected teams in the same room we unleash bold thinking with the power to inspire life-changing -person working gives us the platform we need to connect work at pace and challenge
perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual
flexibility. Join us in our unique and ambitious world.
Why AstraZeneca:
Here curiosity meets courage and software meets science. You will work shoulder to shoulder with researchers data scientists and engineers using cutting-edge technology and rich datasets to help transform complex biology into actionable insight. We bring unexpected teams into the same room to unleash bold thinking and we value kindness alongside ambition so you can stretch yourself while being supported. Your contribution directly advances medicines for people with serious conditions with room to learn grow and when great science comes alive see your work shared with the world.
Call to Action:
Step into a role where your engineering leadership shapes tools that accelerate discoverysend your CV and help build the systems that move science faster to patients!
Date Posted
24-Dec-2025Closing Date
05-Jan-2026AstraZeneca 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.
Required Experience:
Director
AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, ... View more