Knowledge Graph & AI Engineer

About AstraZeneca

AstraZeneca is a global, innovation-driven BioPharmaceutical business that focuses on the discovery, development, and commercialisation of prescription medicines for some of the world's most serious diseases . But we're more than one of the world's leading pharmaceutical companies.

At AstraZeneca we're dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and ignite your entrepreneurial spirit. There's no better place to make a difference to medicine, patients, and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth, and development.

About the Role

We are seeking a highly skilled and experienced Knowledge Graph & AI Engineer to join the Forward Deployed AI group as part of the Knowledge Engineering Team . In this position you will play a critical role in supporting projects and initiatives across different domains within AstraZeneca.

Your primary responsibility will be to develop and oversee the data ingestion, clean-up, enrichment part of the pipeline, and UI implementation for projects that require it. The ideal candidate will possess solid experience in data engineering and analytics, complemented by demonstrated experience in applying AI within healthcare or biological domains.

Key Responsibilities

• Work closely with data scientists, knowledge engineers, domain experts, and other teams to understand their data needs and translate them into clear, manageable technical tasks.
• Support the design, implementation, and maintenance of data ingestion pipelines under the guidance of senior engineers.
• Contribute to the implementation and running of reliable, scalable ETL/ELT workflows to ingest, transform, and load data.
• Assist with data cleansing, normalisation, and transformation activities to prepare datasets for analysis and downstream use.
• Help enrich datasets by applying basic knowledge graph techniques and integrating reference data and ontologies.
• Apply sound data engineering practices and ontology design principles to help keep the Knowledge Graph structure accurate, consistent, and aligned with project requirements.
• Write and optimise Cypher and SQL queries to support data validation, enrichment, and analysis requests.
• Develop and run basic data quality checks and validation routines, escalating issues where necessary.
• Support the preparation and deployment of AI and ML solutions, particularly those that make use of knowledge graphs and LLM-powered applications.
• Support the setup and integration of the Knowledge Graph with LLM-powered applications and related services.
• Help monitor and troubleshoot data pipelines and services, resolving straightforward issues and escalating more complex problems.
• Document data models, ingestion workflows, query patterns, standards, and procedures to ensure work is clearly recorded, reproducible, and easy to share within the team.
• Provide demos and support to internal stakeholders on how to access, query, and interpret data within the Knowledge Graph.
• Participate in continuous improvement activities, learning from feedback and contributing to enhancements of tools, pipelines, and team practices.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Basic proficiency in Python for data processing and scripting.
• Experience building or supporting data pipelines such as ETL/ELT.
• Familiarity with relational databases and SQL.
• Exposure to knowledge graphs or graph databases, gained through projects or coursework.
• Understanding of core concepts in data cleansing, normalisation, and enrichment.
• Exposure to AI/ML concepts and libraries through academic, personal, or internship projects.
• Understanding of software engineering practices such as version control and testing.
• Interest in applying data and AI techniques to healthcare, life sciences, or biology.
• Ability to work with structured and unstructured datasets and to perform exploratory data analysis.
• Strong analytical and problem-solving skills, with attention to detail.
• Ability to work effectively as part of a multidisciplinary team.
• Clear written and verbal communication skills, including documenting work in a structured way.
• Willingness to engage with stakeholders to clarify requirements and share progress.

Good to Have

• Experience with knowledge graph-related projects such as semantic search, entity linking, or ontology-based applications
• Familiarity with semantic technologies and ontologies, ideally in biomedical or clinical domains
• Exposure to cloud platforms or containerisation tools
• Experience from internships, placements, or academic projects in healthcare, pharmaceuticals, or other regulated environments
• Familiarity with frontend development (HTML, CSS, JavaScript, TypeScript, and frameworks like React, Angular, or Vue.js)

If you meet the above qualifications and areapassionate, results-driven individual with the expertise and determination to excel in this challenging role, we would love to hear from you.

Date Posted

23-jul-2026

Closing Date

30-jul-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.