AI Full stack Software Engineer

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As an AI Full Stack Software Engineer with CoverMyMeds, you'll be responsible for developing cutting-edge AI solutions to improve healthcare outcomes. You will collaborate with cross-functional teams to design, develop, and deploy AI models and applications that enhance patient care, streamline clinical workflows, and drive business growth. Your role will involve leveraging advanced technologies such as machine learning, natural language processing, computer vision, and cloud computing to create innovative AI products and services. * Responsibilities: Develop and deliver AI-driven enterprise quality software applications
Build scalable applications integrating Large Language Models and other AI tools (e.g. voice recognition, document parsing, image parsing, text to speech, RAG) into new and legacy codebases
Design and optimize data pipelines and datasets for AI system development and testing
Communicate modern AI concepts (LLMs, vector databases etc.) to non-technical audiences
Iteratively craft effective prompts to maximize LLM performance and implement prompt caching strategies
Maintain prompt libraries & benchmark performance
Fine-tune & serve GPT-family, Llama
Develop AI agents Semantic Kernel
Prototype co-pilot experiences & autonomous workflows
Fully document all work at both the code level and application level
The ability to learn and adapt in a changing environment
Collaborate with other staff and outside stakeholders on large projects
Must be passionate about creating solutions and solving complex problems
Minimum Qualifications: B.S. degree in Computer Science or related engineering discipline, or equivalent experience, and minimum 4+ years of experience in software development
Minimum 2+ years of experience in developing AI-enhanced applications using LLMs, voice, image, or speech models
Must have 2+ years developing AI applications in the healthcare or life sciences domain, including translating clinical/business needs into AI solutions
Critical Skills: AI System Evaluation & Optimization: Proficient in sensitivity metrics (precision, recall, F1-score, AUC-ROC) and MLOps for scalable, cost-efficient AI deployment
RAG Development: Skilled in building RAG systems from scratch or with LangChain/LlamaIndex, using vector databases for context-aware LLM applications
LLM Cost Optimization: Expert in managing LLM costs (token pricing, input/output rates) via prompt caching, batching, and quantization
LLM Knowledge: Deep understanding of LLM advancements (GPT-3.5 vs GPT-4 vs o1/”thinking” models) for informed model selection and tuning
Exceptional analytical skills to extract actionable insights from data
Experience using AI coding tools (e.g. GitHub Copilot, Cursor, Codeium/Windsurf)
Proficiency in Python and AI related python libraries such as OpenAI, TensorFlow, PyTorch
Proficiency in creating Node.js web apps (e.g. Express.js)
Experience with cloud (AWS/GCP/Azure)
Effective communication skills to collaborate with technical, DevOps and product management teams
Experience with Git, Docker, and Kubernetes
We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please Our Base Pay Range for this position $106,900 - $178,100
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Location:
Atlanta

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