PRINCIPAL AI ENGINEER - EVINOVA

Introduction to roleAre you ready to be part of the future of healthcare? Can you think big, be bold, and harness the power of data and AI to solve longstanding life sciences challenges? Then Evinova, a new health tech business part of the AstraZeneca Group might be for you! 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 versatile 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 team with varied strengths 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.
he team is looking for a Principal AI Engineer specializing in applying data science, machine learning and genAI methods to develop innovative AI capabilities underlying multiple products.
The role will focus on the design of complex AI agents, including quantitative experiements on prompting, information retrieval, tool use, memory.
Example projects may include constructing model benchmarks, synthetic data generation, model finetuning, automatic prompt optimization, programmatic promp performance evaluation on a task, automatic LLM-driven online evaluation systems.
The role will interact with product, design, engineering, MLops, and subject matter experts and stakeholders.
AccountabilitiesExamples of projects the team works on include genAI search services, agentic document generation, algorithmic insight generation, optimization, high-frequency and high-dimensional clinical data modeling, clinical trial prediction and much more!Spearhead the development of innovative AI solutions, with a focus on creating novel agentic systems using LLMs.
Ideate, develop, and compare the performance of different tools for agents  (e.
.
search, memory, context compression, communication architectures for agents) Develop automated techniques for designing and evaluating agentic systems.
Systematically discover and test prompt engineering best practices for agents.
Develop specialized observability pipelines to assist with automated evaluation of models and prompts across the model/product lifecycle.
Collaborate in a multidisciplinary environment to align AI initiatives with business objectives and drive digital transformation.
Represent the company's AI expertise at conferences, publications, and industry events.
Essential Skills/ExperiencePh.
.
in a relevant field (such as mathematics, computer science, data science).
4+ years of industry 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.
., TensorFlow, PyTorch, LangChain, LlamaIndex) Extensive experience with AWS services (e.
.
SageMaker, Bedrock, MSK, EKS, OpenSearch).
Deep understanding of agentic AI systems and frameworks (e.
.
agentic design patterns, multi-agent systems, reinforcement learning).
Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences.
esirable Skills/ExperienceDemonstrated 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.
When we put unexpected teams in the same room, we unleash 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.
t AstraZeneca, we are supported with all the tools of a leading pharmaceutical company coupled with an agility mentality.
We are quick to adapt and evolve in our dynamic fields of medicine, science, and technology.
Our work is about disrupting the status quo and thinking critically to drive innovation.
We embrace change and naturally adapt to our ever-evolving industry.
Our inclusive approach celebrates different perspectives which drive our innovation.
We are proud to be part of a value-driven business built on a collaborative culture that supports your ambitions and learning at scale.
eady to make an impact? Apply now to join our journey!Date Posted26-jun-Closing Date10-jul-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.