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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 optimizing AI systems and deploying scalable solutions in the healthcare domain.
Highest-signal resume keywords
AI-Enhanced Application DevelopmentLarge Language Model OptimizationMLOps ExperiencePython ProficiencyHealthcare Domain Expertise
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software DevelopmentAI Application DevelopmentData Pipeline DesignSensitivity Metrics ProficiencyRAG System DevelopmentLLM Fine-TuningNode.js Web Application DevelopmentAI Coding Tools UsagePrompt-Caching StrategiesModel Selection and Tuning
Soft Skills
Effective CommunicationCollaborationAdaptability
Tools & Technologies
OpenAITensorFlowPyTorchGitHub CopilotLangChainLlamaIndexAWSGCPAzureDocker
Industry Keywords
AI ToolsVoice RecognitionDocument ParsingImage ParsingText-to-SpeechVector 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 such as 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 with Semantic Kernel
- Prototype copilot experiences and autonomous workflows
- Fully document work at code and application levels
- Collaborate with staff and outside stakeholders on large projects
- Learn and adapt in a changing environment
- Translate clinical and business needs into AI solutions
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 optimization through prompt caching, batching, and quantization
- Deep understanding of LLM advancements and model selection/tuning
- Experience using AI coding tools such as GitHub Copilot, Cursor, or Codeium/Windsurf
- Proficiency in Python and AI-related libraries including OpenAI, TensorFlow, and PyTorch
- Healthcare domain expertise
- 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 for collaboration with technical, DevOps, and product management teams
- Sponsorship is unavailable presently or in the future
- Priority given to candidates residing in the Atlanta, Georgia, or Columbus, Ohio metropolitan areas
Benefits
Comp & perks- Competitive compensation package
- Annual bonus or long-term incentive opportunities may be offered
- Benefits available through McKesson’s Total Rewards program