McKesson is looking to develop cutting-edge artificial intelligence solutions aimed at enhancing healthcare outcomes, improving patient care, streamlining clinical workflows, and supporting business growth.
Requirements
- At least 2+ years of experience developing AI-enhanced applications using large language models (LLMs), voice, image, or speech models
- Proficiency in Python and AI libraries such as OpenAI, TensorFlow, PyTorch
- Experience with cloud platforms like AWS, GCP, or Azure
- Knowledge of Node.js and web application development (e.g., Express.js)
- Experience with MLOps, model evaluation metrics, and cost optimization strategies for LLMs
- Familiarity with tools like Git, Docker, Kubernetes, and AI coding assistants (e.g., GitHub Copilot)
Responsibilities
- Develop and deliver enterprise-grade AI-driven software applications that meet business needs
- Build scalable applications integrating Large Language Models and other AI tools such as voice recognition, document parsing, image analysis, and text-to-speech functionalities
- Design and optimize data pipelines and datasets for AI system development and testing
- Translate complex AI concepts like LLMs, vector databases, and retrieval-augmented generation into understandable language for non-technical stakeholders
- Iteratively craft and optimize prompts to maximize LLM performance, including prompt caching strategies and prompt library management
- Fine-tune and serve GPT-family models, Llama, and develop AI agents such as Semantic Kernel
- Prototype co-pilot experiences and autonomous workflows to enhance user interactions and operational efficiency
Other
- Minimum of 4+ years of software development experience
- Hands-on experience in healthcare or life sciences domain, translating clinical and business needs into AI solutions
- Strong analytical, communication, and collaboration skills
- Collaborate effectively with cross-functional teams and external stakeholders on large-scale projects
- Continuously learn and adapt to emerging AI technologies and industry best practices
