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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-powered healthcare solutions, with a strong focus on LLMs, data pipeline optimization, and MLOps for scalable deployment. Proficient in Python and AI libraries, capable of translating complex clinical needs into effective AI applications.
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 ProficiencyLLM Fine-TuningPrompt Caching StrategiesNode.js Web Application DevelopmentGitHub Copilot UsageAI Coding Tools ProficiencyVector Database Experience
Soft Skills
Effective CommunicationCollaborationProblem SolvingAdaptability
Tools & Technologies
OpenAITensorFlowPyTorchAWSGCPAzureGitDockerKubernetesLangChain
Industry Keywords
Healthcare ProductsAI SolutionsVoice RecognitionDocument ParsingImage ParsingText-to-SpeechRAG SystemsLLM AdvancementsModel SelectionClinical Needs Translation
Tech Stack
Tools & technologiesAWSAzureDockerGoogle Cloud PlatformJavaScriptKubernetesNode.jsPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Design, develop, and deploy end-to-end AI-powered solutions for healthcare products and services
- 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
- 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 and implement prompt caching strategies to maximize LLM performance
- Maintain prompt libraries and benchmark performance
- Fine-tune and serve GPT-family and Llama models
- Develop AI agents using Semantic Kernel
- Prototype copilot experiences and autonomous workflows
- Fully document work at code and application levels
- Collaborate with staff and external stakeholders on large projects
- Learn and adapt in a changing environment
- Create solutions and solve complex problems
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
- MLOps experience 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 Python libraries including 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 for collaboration with technical, DevOps, and product management teams
- Must be eligible to work without current or future sponsorship
Benefits
Comp & perks- Competitive compensation package
- Annual bonus or long-term incentive opportunities may be offered
- Total Rewards benefits package
- Equal employment opportunities
- Reasonable accommodation for applicants with disabilities