AI Engineer / Senior AI Engineer
AI summary of the role
Design, build, and deploy GenAI and Agentic AI solutions for cancer research, biometrics, clinical research, and broader R&D workflows at a science-led biopharma.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Design, develop, and deploy GenAI and Agentic AI solutions for scientific research, biometrics, clinical trial, and oncology-related workflows
- Build LLM-powered applications using 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 translate user needs into clear technical solutions
What you’ll bring
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Bioinformatics, Statistics, Applied Mathematics, or a related field
- 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
Technologies
Python · LLM · RAG · LangChain · LangGraph · Pydantic-AI · CrewAI · REST APIs · SQL · AWS · Azure · GCP
About AstraZeneca
Science-led biopharma developing and commercializing prescription medicines across oncology, chronic disease, respiratory/immunology, infectious disease, and rare disease, with AI-enabled R&D and global launch scale.
Public · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
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
More from the job description
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, evalu [... source excerpt omitted ...] al-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 G [... source excerpt omitted ...] cs. 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.
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