Principal AI Engineer - Evinova
AstraZenecaAbout the role
The Human-centered AI team at Evinova aims to transform the patient experience and clinical trial process by embedding data science and AI in digital solutions serving clinical trials. We are looking for dedicated individuals to develop ideas into impactful product capabilities that make a difference to patients.
Evinova delivers market-leading digital health solutions that are science-based, evidence-led, and human experience-driven. Thoughtful risks and quick decisions come together to accelerate innovation across the life sciences sector. Be part of a diverse team that pushes the boundaries of science by digitally empowering a deeper understanding of the patients we help. Launch pioneering digital solutions that improve the patients’ experience and deliver better health outcomes. Together, we have the opportunity to combine deep scientific expertise with digital and artificial intelligence to serve the wider healthcare community and create new standards across the sector.
As Principal AI Engineer, you'll design and implement sophisticated agentic AI systems that power next-generation healthcare solutions. Working at the intersection of AI research and real-world healthcare applications, you'll build intelligent agents that can reason, plan, and act autonomously to solve complex clinical challenges.
What makes this role compelling:
- Lead challenging projects in agentic AI, LLM orchestration, and multi-agent systems
- Build AI agents that directly impact patient care and clinical trial efficiency
- Collaborate with product teams, clinical experts, and ML engineers in a fast-paced environment
- Develop automated evaluation systems, prompt optimization techniques, and advanced agent architectures
- Contribute to the AI in life sciences community through publications, conferences, and open-source work
Example impactful projects include: Intelligent AI agents for clinical document generation, advanced search systems for medical research, clinical trial optimization tools, synthetic patient data generation, and multi-modal healthcare AI assistants.
Typical Responsibilities:
Design Advanced AI Systems
- Build and deploy sophisticated agentic AI solutions using state-of-the-art LLMs
- Develop novel approaches to agent memory, tool use, and multi-agent collaboration
Drive Technical Innovation
- Create automated techniques for agent design, evaluation, and optimization
- Systematically discover and validate effective prompt engineering approaches for agentic systems
- Build specialized observability pipelines for continuous model and agent performance monitoring
Lead Cross-Functional Collaboration
- Partner with product, design, and clinical teams to translate AI capabilities into impactful healthcare solutions
- Mentor engineers and contribute to AI strategy across the organization
Contribute to the Field
- Share expertise at conferences and through technical publications
- Contribute to open-source projects and help advance standard methodologies in healthcare AI
Essential requirements :
- Ph.D. in a relevant field (such as mathematics, computer science, data science).
- 4+ years of indstry experience in applied machine learning, with a strong focus on deep learning, NLP, and generative AI.
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