AI Engineer – Connected Insights at AstraZeneca

Santanyí, Balearic Islands, Spain -

Full Time

Start Date

Immediate

Expiry Date

09 Jan, 26

Salary

0.0

Posted On

11 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering, Machine Learning, Python, Data Structures, Algorithms, API Design, Distributed Systems, Microservices, NLP, Image Analysis, Graph Theory, Generative AI, Collaboration, Problem-Solving, Cloud Computing, Software Engineering

Industry

Pharmaceutical Manufacturing

Description

About the team The Connected Insights service is an internal, high-profile, bespoke data & AI service built in collaboration with our in-house competitive intelligence professionals. It is transforming how competitive intelligence is created, disseminated and consumed across AstraZeneca into a rich, digital, interconnected and on-demand experience. Through the use of data pipelines, knowledge graph, interactive visualisations and machine learning, we seek to integrate key external and internal data sources, generate complex interactive information, and transform how our teams of competitive intelligence professionals create and share insights. We value creating an excellent customer experience, reliable data, and effective engineering practises. About the role We are seeking a talented and motivated AI Engineer to join Connected Insights. As an AI Engineer, you'll be at the forefront of developing and deploying AI products that drive business and scientific insights. Your work will involve building models using both foundational and cutting-edge methods, processing structured and unstructured data, and collaborating closely with internal stakeholders to solve complex problems in competitive intelligence and strategy. Our projects range from developing intelligent AI-driven systems such as virtual assistants to applying advanced data science and analytics techniques that support decision-making and optimize business outcomes. Collaborating with cross-functional teams, you will understand client requirements and develop these customised AI solutions to address their specific needs and partner with external AI companies where required. Key Responsibilities • Drive the implementation of advanced modelling algorithms (e.g., classification, regression, clustering, NLP, image analysis, graph theory, generative AI) to generate actionable business insights. • Leadership: mentor AI scientists, plan and supervise technical work, collaborate with stakeholders. • Work within an agile framework and in cross-functional teams to align AI solutions with business goals. • Engage internal stakeholders and external partners for the successful delivery of AI solutions. • Continuously monitor and optimize AI models to improve accuracy and efficiency (scalable, reliable, and well-maintained). • Document processes, models, and key learnings & contribute to building internal AI capabilities. • Ensure AI models adhere to ethical standards, privacy regulations, and fairness guidelines. Required Skills MS or PhD or equivalent experience in AI, Computer Science or related areas Proficiency in Python and software engineering best practices. Experience with vector databases, NER, and similarity search systems. Experience with distributed systems and microservices. Strong understanding of data structures and algorithms. Knowledge of API design and development. Experience working with a multi-disciplinary team. Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills. Desirable Skills Machine Learning Experience developing and deploying agentic AI systems, including autonomous agents and multi-agent workflows. Hands-on expertise with Retrieval Augmented Generation (RAG) techniques and their integration with Large Language Models. Practical experience fine-tuning, customizing, or implementing Large Language Models (LLMs) such as GPT, Llama, or similar. Knowledge of ML monitoring and observability. Experience with real-time inference optimisation. Software Engineering Contributions to open-source ML projects or libraries. Experience with high-performance computing. Knowledge of software design patterns. Cloud & Infrastructure Experience with ML deployment platforms (KubeFlow, MLflow). Knowledge of serverless architecture patterns. Understanding of cloud cost optimisation for ML workloads. Experience with infrastructure-as-code (Terraform, CloudFormation). 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. At AstraZeneca, we connect across the business to drive disruptive transformation through data-led innovations. Our work empowers efficient processes and quality decision-making, impacting patient outcomes globally. Collaborate with leading experts in specialist communities to expand your knowledge and contribute to novel solutions. Here, your contributions are recognized from the top down, providing endless development opportunities. Ready to make an impact? Apply now to join our team! Date Posted 10-oct-2025 Closing Date 24-oct-2025 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.

Responsibilities

The AI Engineer will develop and deploy AI products that drive business and scientific insights, working on projects that include intelligent AI-driven systems and advanced data science techniques. They will collaborate with cross-functional teams to customize AI solutions and ensure successful delivery.