Lead AI & Data Engineer – APD Platform

About the role

Are you ready to power the business to have a bigger impact on patients lives Embrace the novel opportunity to work at a business that puts patients Early Science we have highly skilled scientists in our labs who experiment and support complex drug projects. The environment is driven by scientific and technical innovation with a high level of diversity in workflows data and vendors. The Accelerated Pharmaceutical Development (APD) platform drives digitization in two business areas cutting across both complex synthetic modalities & biologics that combined deliver AstraZenecas chemistry manufacturing and controls (CMC) which are crucial activities when developing new pharmaceutical products.

AstraZenecasR&D ITorganisation is seeking aLead AI & Data Engineerto join theAPD Platform Data & AI team in Barcelona. This senior individual-contributor role will provide hands-on technical leadership while supporting the design development and operation of scalable data and artificial intelligence capabilities that enable research and development teams to access manage analyse and derive value from trusted data.

As part of the APD Platform you will work with data engineers AI specialists software engineers architects product managers scientists and business stakeholders to deliver secure reliable and reusable platform capabilities. You will contribute to solutions that support data-driven decision-making advanced analytics machine learning and emerging AI use cases across the R&D organisation.

Key responsibilities

• You will design develop test deploy and maintain production-quality data and AI engineering solutions for theAPD Platform. This will include developing data pipelines data products analytical services machine learning capabilities and AI-enabled applications that meet business scientific quality security privacy and regulatory requirements.
• You will collaborate with stakeholders to understand user needs define technical requirements assess implementation options and deliver solutions that are scalable maintainable observable and fit for purpose. You will contribute to platform architecture engineering standards reusable patterns and technical decisions that support the continued evolution of APD Platform capabilities.
• You will prepare integrate transform and manage data from structured and unstructured sources. You will implement data quality validation lineage metadata access control and governance measures to help ensure that data is discoverable reliable secure and appropriately managed.
• You will contribute to the development and operationalisation of AI and machine learning solutions including model deployment monitoring evaluation versioning and lifecycle management. This may include working with large language models retrieval-augmented generation prompt engineering AI agents and other generative AI technologies.
• You will apply modern engineering and DevOps practices including continuous integration and delivery automated testing infrastructure as code containerisation monitoring alerting and incident resolution. You will also contribute to technical documentation peer reviews knowledge sharing and continuous improvement across the platform engineering community.
• This role requires strong technical leadership across the APD Platform Data & AI team. You will provide technical direction guide solution design and architecture and ensure that engineering decisions align with platform strategy enterprise standards and scientific and business priorities.
• You will lead by example through hands-on engineering high-quality technical reviews and clear decision-making. You will establish and promote reusable patterns engineering standards and good practices for data AI software delivery security reliability and operational excellence.
• You will mentor engineers facilitate constructive technical discussions resolve complex technical challenges and help teams make pragmatic trade-offs. You will influence architects product managers scientists vendors and other engineering teams building alignment and shared accountability for sustainable outcomes.

Essential experience and skills

• You will have substantial experience indata engineering AI engineering software engineering or a closely related discipline with a track record of providing technical leadership and delivering production-quality solutions in a complex enterprise environment.
• You should have strong programming experience inPythonand/or another modern programming language together with solid knowledge ofSQL data modelling APIs version control automated testing and software development practices.
• You will have experience designing and implementing data pipelines data products or data platforms using cloud technologies. Familiarity with one or more major cloud platforms and associated services for storage compute databases analytics machine learning identity and monitoring is expected.
• You should understand machine learning engineering andMLOpsprinciples including model development workflows deployment monitoring reproducibility performance evaluation and responsible lifecycle management. Experiencedeveloping or operationalising AI/ML solutions including generative AI applications LLM integration retrieval-augmented generation model evaluation or AI service deployment would be valuable.
• You will be comfortable with engineering and DevOps practices such asCI/CD infrastructure as code containerisation observability and agile delivery. Experience with technologies such as Spark Docker Kubernetes Terraform Git-based workflows or comparable tools would be beneficial.
• You will be able to communicate complex technical concepts clearly to both technical and non-technical audiences. Collaboration structured problem-solving stakeholder engagement and the ability to work effectively across multidisciplinary and geographically distributed teams are essential.

Desirable experience

• Experience in thepharmaceutical biotechnology healthcare life sciences or another highly regulated industry would be beneficial. Knowledge of R&D processes scientific data laboratory data clinical development real-world data or regulated technology environments would also be valuable.
• Additional experience with data governance privacy information security FAIR data principles responsible AI knowledge graphs semantic data models or scientific computing would be advantageous. Familiarity with platform engineering enterprise architecture product-oriented delivery or self-service data and AI platforms would further support success in the role.
• Experience in following technologies is desirable: PowerBI Startburst Snowflake AWS Glue Terraform LangChain LangGraph LangSmith FastAPI Pydantic Pandas
• A degree or equivalent professional experience incomputer science engineering data science mathematics life sciences or a related subject is preferred.

What success looks like

Success in this role will mean delivering reliable secure and reusable data and AI capabilities for theAPD Platformthat are adopted by R&D teams and provide measurable value.

You will help improve the accessibility quality governance and usability of R&D data while enabling the secure and scalable use of AI. You will also help strengthen engineering standards accelerate delivery through automation and reusable patterns and build trusted relationships with scientific business and technology stakeholders.

Why AstraZeneca

At AstraZeneca technology and data are central to our ambition to transform the future of healthcare. WithinR&D IT and the APD Platform you will have the opportunity to work on meaningful technical and scientific challenges collaborate with experts across disciplines and contribute to solutions that support the discovery and development of medicines for patients worldwide.

We are committed to creating an inclusive environment where diverse perspectives are valued and everyone can contribute develop and thrive.

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

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.