AI Engineer / Senior AI Engineer

Position Overview
We are seeking AI Engineers to join the Data Science team to design, build, and deploy GenAI and Agentic AI solutions for cancer research, biometrics, clinical research, and broader R&D workflows.
The role will work closely with data scientists, data integration engineers, and scientific stakeholders to translate complex research needs into practical AI-enabled systems. Example solution areas include LLM-powered workflow automation, RAG-based knowledge retrieval, structured information extraction, AI-assisted data analysis, and decision-support applications.
For senior candidates, the role will also involve leading technical design, guiding solution architecture, mentoring junior team members, and helping move high-value AI use cases from prototype toward production.
Main Duties and Responsibilities
Design, develop, and deploy GenAI and Agentic AI solutions for scientific research, biometrics, clinical trial, and oncology-related workflows
Build LLM-powered applications using techniques such as prompt engineering, tool use, structured output generation, RAG, and agentic workflow orchestration
Integrate AI solutions with existing data platforms, databases, APIs, and enterprise systems
Collaborate with scientific, clinical, and data stakeholders to understand user needs and translate them into clear technical solutions
Develop prototypes and MVPs, evaluate their performance, and iterate based on user feedback and business value
Support appropriate documentation, testing, traceability, and human oversight for AI solutions in a regulated R&D environment
Stay current with emerging GenAI and Agentic AI technologies and assess their applicability to real-world R&D use cases
Senior level: Lead technical design decisions, guide architecture choices, mentor junior engineers, and support the transition of selected solutions toward production
Requirements by Level
Education
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Bioinformatics, Statistics, Applied Mathematics, or a related field.
Experience
Junior Level
1–3 years of experience in software engineering, data science, machine learning, AI application development, or bioinformatics
Hands-on experience with Python and practical exposure to LLMs, data pipelines, APIs, or AI-enabled applications
Strong willingness to learn and apply emerging GenAI technologies in scientific or healthcare-related settings
Senior Level
5+ years of experience in AI, machine learning, data science, software engineering, or related fields
Proven experience delivering AI/ML, GenAI, or data-driven solutions in real-world business, research, or enterprise environments
Experience leading technical design, making architecture decisions, and guiding projects from problem definition to prototype, evaluation, and deployment
Ability to mentor junior engineers and collaborate effectively across data science, engineering, and domain expert teams
Essential Technical Skills
Strong Python programming skills for AI application development, data processing, and workflow automation
Hands-on experience with LLM-based applications, including prompt engineering, structured outputs, tool use, or agentic workflows
Experience with RAG architectures, embeddings, vector databases, document processing, or knowledge retrieval systems
Familiarity with Agentic AI frameworks such as LangChain, LangGraph, Pydantic-AI, CrewAI, or similar tools
Experience working with REST APIs, SQL databases, and data integration workflows
Understanding of software engineering best practices, including version control, testing, documentation, and CI/CD
Familiarity with cloud platforms or enterprise deployment environments, such as AWS, Azure, or GCP
Basic awareness of data privacy, compliance, validation, and responsible AI considerations in healthcare, life sciences, or other regulated environments
Desirable Skills
Experience applying AI or data science in clinical research, biometrics, oncology, cancer research, drug development, or healthcare workflows
Experience designing evaluation approaches for LLM or GenAI systems, including accuracy, retrieval quality, usability, robustness, and human review
Experience with workflow orchestration, AI agents, automation pipelines, or multi-step decision-support systems
Familiarity with bioinformatics, genomics, computational biology, computational pathology, or medical imaging use cases
Experience with TypeScript, JavaScript, or front-end development for building user-facing AI applications
Understanding of model optimization, fine-tuning, or domain adaptation techniques
Familiarity with data privacy regulations and compliance expectations such as HIPAA, GDPR, GxP, or internal enterprise governance processes
Personal Attributes
Strong problem-solving skills and analytical thinking
Ability to work independently while collaborating effectively in cross-functional teams
Strong communication skills and ability to explain technical concepts to non-technical stakeholders
Curiosity and eagerness to learn emerging AI technologies
Attention to detail and commitment to building reliable, usable, and well-documented solutions
Passion for applying AI to advance cancer research, clinical development, and patient outcomes
Date Posted
09-9月-2026
Closing Date
25-9月-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.