Principal AI Engineer - Evinova

WHY JOIN US?

Evinova is a health-tech business focused on accelerating better health outcomes by advancing digital transformation across the life sciences sector. By combining science-based expertise, evidence-led rigor, and deep human insight, we design digital solutions that enable healthcare to work better for everyone.
 

Operating at the intersection of healthcare, technology, data, and analytics, we are helping unlock the full potential of digital health, transforming how clinical research is conducted, how care is delivered, and how patients experience healthcare. Our solutions are built to scale, driving efficiency, improving decision-making, and ultimately delivering better outcomes for patients worldwide.
 

At Evinova, we are driven by a shared purpose to transform health through data and digital innovation. Our teams collaborate across disciplines to solve complex challenges, continuously learning and evolving in a fast-paced, high-impact environment.
 

We also recognize the importance of flexibility and balance. Our ways of working support both individual needs and team collaboration. To foster connection and collaboration, employees are expected to work from the office three days per week, creating opportunities for in-person teamwork, innovation, and meaningful connection.

Introduction to Role:
 

As Principal AI Engineer, you'll design and implement sophisticated agentic AI systems that power next-generation life sciences 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 clinical trials, drug discovery, and ultimately patient care

• 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.

Accountabilities:

• 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

  • Build sophisticated NLP systems for retrieval, information extraction, structured generation, graph reasoning.
     

• 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 best practices in healthcare AI

Essential Skills/Experience:

• Master's Degree 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.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 complex technical concepts to both technical and non-technical audiences

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