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. 

• Extensive prior experience exploring and testing language model behavior, prompting and building products with language models. 

• Expert knowledge of Python and advanced ML/LLM frameworks (e.g., TensorFlow, PyTorch, Google ADK, Crewai,  LangChain, LlamaIndex) 

• Extensive experience with AWS services (e.g. SageMaker, Bedrock, MSK, EKS, ECS, OpenSearch). 

• Deep understanding of agentic AI systems and frameworks (e.g. agentic design patterns, multi-agent systems, reinforcement learning). 

• Excellent communication skills with the ability to articulate sophisticated technical concepts to both technical and non-technical audiences 

Desirable requirements:

• Demonstrated technical leadership experience, including successful delivery of large-scale AI projects. 

• Experience developing complex agentic systems using LLMs.  

• Experience with low-level languages used for implementing high-performance ML code (C/C++, Rust, CUDA, etc.) 

• Contributions to open-source AI projects or development of proprietary AI frameworks. 

• Expertise in areas such as few-shot learning, meta-learning, explainable AI. 

• Experience with AI ethics, responsible AI practices, and navigating regulatory landscapes for AI deployment in the life science industry. 

In-Office/Hybrid Statement:

When we put unexpected teams in the same room, we ignite bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

As AstraZeneca continues to put patients at the forefront of our mission, we are excited for our move to Kendall Square/Cambridge in 2026. Find out more information here: Kendall Square Press Release

Why AstraZeneca? 

At AstraZeneca when we see an opportunity for change, we seize it and make it happen, because any opportunity no matter how small, can be the start of something big. Delivering life-changing medicines is about being entrepreneurial - finding those moments and recognising their potential. Join us on our journey of building a new kind of organisation to reset expectations of what a bio-pharmaceutical company can be. This means we’re opening new ways to work, pioneering innovative methods and bringing unexpected teams together. Interested? Come and join our journey.  

Date Posted

Closing Date