AI Engineer / Senior AI Engineer

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Bioinformatics, Statistics, Applied Mathematics, or a related field.

Experience

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

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

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

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

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

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.