Full Stack Engineer
AI in this role
Design and build cloud-native applications and data products to accelerate AI/ML-driven biologics and drug discovery workflows.
GCL: D2
Introduction to role:
Are you ready to build cloud-native products that accelerate antibody discovery and help bring medicines to patients faster! Join us to turn advanced data and AI into real-world impact by designing end-to-end solutions scientists love to use.
You will be part of a global, high-calibre team of software, data, and MLOps engineers, architects, product leaders, and scientists building an Augmented Biologics Discovery Platform. You will shape the experience and the architecture, turning complex scientific workflows into intuitive, production-grade software that shortens the path from idea to clinical candidate.
Working side by side with product, design and scientific users, you will create scalable services, data products and applications in the cloud. How would you design a cohesive, delightful experience that researchers choose every day because it makes their work faster, clearer and more insightful?
Accountabilities:
- Full-Stack Solution Design: Own the design and implementation of scalable, cloud-native applications that meet scientists’ requirements end to end.
- AI/ML Data Products: Deliver production-grade data products that enable and accelerate AI/ML use cases in discovery.
- Product and UX Innovation: Build novel features that solve long-standing drug discovery problems with experiences that feel seamless and unified.
- Cross-Functional Collaboration: Work closely with product, design, data science, and scientific teams to build cutting-edge services and user journeys.
- Architecture and Data Models: Propose and implement changes to data models, core architecture, and the codebase to improve quality and velocity.
- Full-Stack Delivery: Contribute across all layers of the stack, even where you are less experienced, to move the product forward.
- Agile Ways of Working: Advance modern, agile software practices and help foster a vibrant engineering culture.
- Platform Reliability: Plan, implement and support core infrastructure to improve scalability, reliability, performance, and availability.
- Engineering Excellence: Champion rigorous practices including code reviews, automated testing, logging, monitoring, and alerting.
- Learning and Mentorship: Stay on top of tech trends, experiment, engage with internal and external communities, and mentor peers.
- Critical Problem Solving: Apply structured analysis and sound judgment to propose robust solutions to engineering challenges.
Essential Skills/Experience:
- Experience in designing end-to-end full stack software in cloud
- Deep expertise in Java and Python. Additionally, expertise in other programming languages like C++, Node.js will be advantageous
- Experience in at least one major web development framework from Spring, Flask, Django, and beyond
- Strong front end skills with one of the major front end frameworks from React, Angular or Vue.js
- Additional front-end skills in CSS as well as some related CSS framework like Bootstrap
- Experience working with relational and/or NoSQL databases and knowledge of query optimization techniques
- Proficiency in Linux environments
- Demonstrable high proficiency in data structures and design patterns, as well as associated antipatterns. Be able to defend, compare, and contrast these decisions
- Demonstrable abilities with the coding best practices including testing, code review, and version control
- CI/CD experience with some automation tooling like Jenkins, TravisCI, Github actions, etc.
- Experience of data analysis – profiling, investigating, interpreting, and documenting data structures
- Excellent teamworking, verbal, and written communication skills
- Experience with Docker and Kubernetes
Desirable Skills/Experience:
- Familiarity with Computational Biology/Bioinformatics concepts
- Basic understanding of Machine Learning concepts and MLOps
- Experience in microservice architecture
- Experience with message queuing (RabbitMQ, SQS, etc.)
- Experience with GitOps for Kubernetes
Why AstraZeneca:
Here you will join a fast-moving, digitally savvy community that blends bold ambition with genuine support. We work in unexpected combinations—scientists, engineers, designers and product leaders in the same room—turning ideas into working software that changes how decisions are made across discovery. You will apply modern engineering, data and design thinking to real problems, see your work used at global scale, and feel its impact on patients. We back curiosity with ownership, value kindness alongside ambition, and give you the space to move quickly while doing things the right way.
Call to Action:
If you are ready to build software that advances science and your career, send your CV today and help us transform biologics discovery for patients worldwide!
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Date Posted
30-Sept-2026Closing Date
13-Oct-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.
How we rate this
Full Stack Engineer at AstraZeneca rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where full stack was part of your work. What did you do?
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- Tell me about a project where cloud native was part of your work. What did you do?
- Tell me about a project where software engineering was part of your work. What did you do?
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- List these exact terms on your resume: ML Ops, Full Stack, Machine Learning, Cloud Native, and Software Engineering. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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