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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** CARET HEALTH INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Clinical Data Repository, Cloud Computing, Data Structures, Python (Programming Language), Operational Data Store, Tensorflow, Pytorch, Fast Healthcare Interoperability Resources, Large Language Models, Multi-Agent Systems, Model Validation, Scikit Learn, Kubernetes, HuggingFace, Machine Learning Operations, Virtual Agents, Data Pipelines, Automation Anywhere - **Published:** June 12, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=8d659678f08ff255 ## About the Role Do you have experience in Research?, * 5+ years of experience building and deploying ML or AI systems in production, ideally in a healthcare, health tech, or regulated data environment. * Strong Python skills and hands-on experience with modern ML frameworks (PyTorch, HuggingFace, scikit-learn); fluency with LLM APIs and fine-tuning workflows. * Hands-on experience building agentic AI systems using orchestration frameworks such as LangGraph, CrewAI, AutoGen, or the Anthropic Agent SDK; comfortable reasoning about agent memory, tool use, failure modes, and multi-agent coordination in production. * Experience designing orchestration layers that coordinate multiple AI models or agents, manage state across steps, enforce guardrails, and support auditability - especially in environments where reliability is non-negotiable. * Experience working with clinical data formats (EHR data structure, FHIR) and an understanding of HIPAA compliance requirements are strong pluses. * Cloud deployment experience (AWS or GCP), including model serving, pipeline orchestration, and monitoring. * Comfort operating in a startup environment: you scope your own work, move quickly, and know when to build vs. buy. * Clear communicator who can explain model behavior and trade-offs to nontechnical stakeholders. ## Description Caret Health is looking for a Senior AI Engineer to take a foundational role in building AI systems that improve healthcare delivery and patient engagement. You will own the design, development, and deployment of intelligent agents and the orchestration layer that powers them - turning complex clinical and operational data into reliable, production-grade AI products. Working closely with product, engineering, and clinical stakeholders, you will define how AI is structured and scaled at Caret Health., * Design, develop, and deploy models tailored to healthcare use cases, including clinical text understanding, predictive analytics, and care workflow automation. * Architect and maintain the AI orchestration layer - defining how agents are triggered, how they hand off context, manage state, and how human-in-the-loop checkpoints are enforced in clinically sensitive workflows. * Design and implement multi-agent systems that coordinate AI workflows across Caret's platform, from patient intake and triage to clinical decision support and operational automation. * Own the end-to-end model lifecycle - from research and training through evaluation, deployment, and monitoring in production environments. * Build and maintain robust, HIPAA-compliant data pipelines that process structured and unstructured clinical data at scale. * Collaborate with product and engineering to integrate AI capabilities directly into Caret's core platform, ensuring models are reliable, interpretable, and performant. * Partner with clinical and operational stakeholders to translate domain problems into well-scoped AI solutions. * Stay current with advances in LLMs, agentic AI, and healthcare-specific AI research; evaluate and prototype emerging approaches using frameworks such as LangGraph, CrewAI, or the Anthropic Agent SDK. * Define and uphold best practices for model evaluation, safety, fairness, and auditability in healthcare contexts. ## Related Videos - [AI in High-Stakes Industries: Lessons Learned](https://www.wearedevelopers.com/videos/100253-ai-in-high-stakes-industries-lessons-learned) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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