- Design and maintain AI‑driven infrastructure solutions supporting AI and machine‑learning services, model hosting, automation, and enterprise integrations.
- Build and enhance automation and operational tooling using Python and PowerShell for AI and ML platforms.
- Provision, configure, and operate AI platform components including Azure OpenAI, AI Search, Functions, Logic Apps, App Services, Storage, Tables, Key Vault, and Log Analytics.
- Enable infrastructure required for ML model training, deployment, and inference workloads.
- Implement repeatable and governed deployments using Infrastructure‑as‑Code and CI/CD practices.
- Support AI and ML model integrations from an infrastructure, runtime reliability, and scalability standpoint.
- Establish monitoring, logging, and alerting for AI/ML workloads to ensure platform availability and proactive issue detection.
- Apply security, compliance, and cost governance controls relevant to AI and ML platforms.
- Create and maintain runbooks, SOPs, and operational documentation for AI infrastructure operations.
- Strong experience with Python and PowerShell for automation and infrastructure engineering use cases.
- Working knowledge of Machine Learning concepts, including model lifecycle, training vs inference, model endpoints, and performance considerations.
- Experience enabling and operating AI/ML‑supporting infrastructure platforms.
- Understanding of AI and ML platform components such as model endpoints, AI APIs, inference services, and supporting infrastructure layers.
- Experience working with CI/CD pipelines (GitHub Actions or Azure DevOps).
- Knowledge of identity, observability, governance, and operational standards required to run AI/ML platforms reliably.
- Strong troubleshooting, operational mindset, and documentation skills.
- Exposure to Infrastructure‑as‑Code tools such as Terraform.
- Familiarity with GitHub‑based workflows for automation and deployments.
- Awareness of MLOps practices such as model registries, deployment pipelines, and lifecycle automation.
- Experience with Application Insights, Log Analytics, or similar observability tools.
- Understanding of AI/ML governance, secure secrets management, and cost‑optimization practices.
- Opportunity to be part of an AI‑first engineering team focused on AI and ML infrastructure enablement.
- Exposure to enterprise‑scale AI/ML platforms, covering enablement, standardization, and operational scale.
- Role influence on how AI infrastructure is designed, governed, monitored, and evolved.
Working in an evolving healthcare setting, we use our shared expertise to deliver innovative solutions. Our fast-growing team has opportunities to learn and grow through rewarding interactions, collaboration and the freedom to explore professional interests.
Our associates are given valuable opportunities to contribute, to innovate and create meaningful work that makes an impact in the communities we serve around the world. We also offer a culture of excellence that drives customer success and improves patient care. We believe in giving back to the community and offer a competitive benefits package. To learn more, visit: r1rcm.com
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What We Do
R1 is a leading provider of technology-driven solutions that transform the patient experience and financial performance of healthcare providers R1’s proven and scalable operating models seamlessly complement a healthcare organization’s infrastructure, quickly driving sustainable improvements to net patient revenue and cash flows while reducing operating costs and enhancing the patient experience.
