AI Developer

Position Summary: We are seeking an experienced AI Developer to design, develop, validate, and deploy advanced artificial intelligence solutions that enhance healthcare operations, clinical workflows, patient engagement, and business performance. This role combines expertise in machine learning, generative AI, software engineering, and healthcare data systems to create scalable, secure, and compliant AI-driven applications. The ideal candidate will have hands-on experience with modern AI platforms, including Large Language Models (LLMs) such as Claude (Anthropic), OpenAI, and other enterprise AI technologies, with the ability to translate complex healthcare challenges into practical and measurable solutions.

Key Responsibilities: Design, develop, test, and deploy AI/ML solutions supporting healthcare use cases, including clinical documentation, patient communications, predictive analytics, care coordination, revenue cycle optimization, and workflow automation. Build and maintain generative AI applications leveraging Large Language Models (LLMs) such as Claude, OpenAI, Gemini, and related AI platforms. Develop and optimize prompt engineering frameworks, retrieval-augmented generation (RAG) architectures, and AI-powered knowledge management solutions. Collaborate with clinicians, operational leaders, data engineers, product teams, and compliance stakeholders to identify opportunities for AI-driven improvements. Build secure and scalable data pipelines utilizing structured and unstructured healthcare data, including EHR, claims, laboratory, operational, and patient communication datasets. Integrate AI applications into existing healthcare platforms, workflows, and enterprise systems while ensuring high performance and user adoption. Evaluate model accuracy, explainability, fairness, reliability, and risk factors throughout the AI lifecycle. Implement monitoring and governance processes to detect model drift, performance degradation, and compliance concerns. Maintain detailed technical documentation for AI systems, model validation, governance controls, deployment procedures, and audit requirements. Support HIPAA-compliant development practices and ensure secure handling of protected health information (PHI).Stay current with advancements in healthcare AI, machine learning, LLM technologies, and responsible AI frameworks.

Required Qualifications: Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Biomedical Informatics, or related field.3+ years of experience developing machine learning, deep learning, natural language processing (NLP), or generative AI solutions. Strong proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, Hugging Face, or similar technologies. Experience building and consuming REST APIs, working with cloud platforms, databases, and distributed applications. Experience deploying production-grade AI applications within secure enterprise environments. Strong understanding of data privacy, security principles, secure coding practices, and healthcare compliance requirements. Excellent problem-solving, analytical, communication, and stakeholder management skills.

Generative AI & Claude Experience: Demonstrated knowledge and hands-on experience with Claude (Anthropic AI) for enterprise generative AI solutions, conversational AI, document analysis, content generation, and workflow automation. Experience designing and optimizing prompts within Claude to improve response quality, consistency, factual accuracy, and operational efficiency. Knowledge of Claude APIs, integrations, model selection strategies, and enterprise AI deployment considerations. Experience evaluating and comparing AI model outputs across platforms including Claude, OpenAI, Gemini, and other emerging LLM technologies. Familiarity with Retrieval-Augmented Generation (RAG), vector databases, semantic search, embeddings, and AI agent frameworks utilizing Claude models.

Healthcare & Technical Experience: Experience working with healthcare interoperability standards including HL7, FHIR, CDA, and EHR systems. Familiarity with HIPAA, HITECH, healthcare compliance programs, and healthcare data governance. Experience implementing MLOps practices including CI/CD, model monitoring, model versioning, deployment pipelines, and reproducibility frameworks. Understanding of Responsible AI principles, including explainability, transparency, bias mitigation, human oversight, and regulatory compliance. Master's degree or advanced certification in Artificial Intelligence, Data Science, Health Informatics, Biomedical Engineering, or related discipline.