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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing AI-driven applications, particularly with Large Language Models and AI tools, while effectively communicating complex concepts to diverse audiences. Proficient in data pipeline optimization and MLOps for scalable AI deployment, with a strong analytical ability to derive insights from data.
Highest-signal resume keywords
AI-Enhanced Application DevelopmentLarge Language Model ExpertiseMLOps ExperiencePython ProficiencyHealthcare Domain Expertise
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Software DevelopmentData Pipeline OptimizationSensitivity MetricsLLM Cost ManagementPrompt CachingNode.js Web Application DevelopmentAI Coding ToolsGitDockerKubernetes
Soft Skills
Effective CommunicationAnalytical SkillsCollaboration
Tools & Technologies
OpenAITensorFlowPyTorchAWSGCPAzureLangChainLlamaIndexGitHub CopilotCursor
Industry Keywords
AI ToolsVoice RecognitionDocument ParsingImage ParsingText to SpeechRAG SystemsVector DatabasesHealthcare
Tech Stack
Tools & technologiesAWSAzureDockerGoogle Cloud PlatformJavaScriptKubernetesNode.jsPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Develop and deliver AI-driven enterprise-quality software applications
- Build scalable applications integrating Large Language Models and AI tools, including voice recognition, document parsing, image parsing, text to speech, and RAG, into new and legacy codebases
- Design and optimize data pipelines and datasets for AI system development and testing
- Communicate modern AI concepts, including LLMs and vector databases, to non-technical audiences
- Craft effective prompts to maximize LLM performance and implement prompt caching strategies
- Maintain prompt libraries and benchmark performance
- Fine-tune and serve GPT-family and Llama models
- Develop AI agents using Semantic Kernel
- Prototype co-pilot experiences and autonomous workflows
- Fully document work at code and application levels
- Collaborate with staff and outside stakeholders on large projects
- Create solutions and solve complex problems in a changing environment
Requirements
What you’ll need- Minimum 2+ years of experience in software development
- Minimum 2+ years of experience developing AI-enhanced applications using LLMs, voice, image, or speech models
- B.S. degree in Computer Science or related engineering discipline, or equivalent experience
- Proficiency in sensitivity metrics: precision, recall, F1-score, and AUC-ROC
- Experience with MLOps for scalable, cost-efficient AI deployment
- Experience building RAG systems using LangChain/LlamaIndex and vector databases
- Expertise in LLM cost management through prompt caching, batching, and quantization
- Deep understanding of LLM advancements and model selection/tuning
- Exceptional analytical skills to extract actionable insights from data
- Experience using AI coding tools such as GitHub Copilot, Cursor, or Codeium/Windsurf
- Proficiency in Python and AI-related Python libraries such as OpenAI, TensorFlow, and PyTorch
- Healthcare domain expertise and ability to translate clinical/business needs into AI solutions
- Proficiency creating Node.js web applications, such as Express.js
- Experience with AWS, GCP, or Azure
- Experience with Git, Docker, and Kubernetes
- Effective communication skills to collaborate with technical, DevOps, and product management teams
- Ability to work in the United States without sponsorship; McKesson is unable to provide sponsorship presently or in the future
Benefits
Comp & perks- Competitive compensation package
- Annual bonus or long-term incentive opportunities may be offered
- Equity may be included as part of total rewards
- Reasonable accommodation for job search or application, where needed