Associate Director of Software Engineering - Scientific & AI Tools

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 Model–powered 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 Model–powered 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 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.

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 discovery—send your CV and help build the systems that move science faster to patients!

Date Posted

24-Dec-2025

Closing Date

05-Jan-2026

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.

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 authorisation and employment eligibility verification requirements.