Lead AI Solutions Engineer

• Design scalable, secure, and resilient cloud applications with a strong understanding of distributed systems, APIs, and microservices.
• Design and implement automated CI/CD pipelines using platforms such as Azure DevOps, GitHub Actions, GitLab, or Jenkins.
• Leverage Generative AI tools to accelerate coding, testing, documentation, and solution development.
• Maintain end-to-end ownership of architected products and systems.
• Move between high-level architecture and hands-on implementation as needed.
• Ensure AI solutions are integrated within Epic for a seamless user experience.

Experience: 10+ years of experience in a relevant field. Relies on extensive experience to plan and accomplish tasks. May lead multiple layers of resources., * Deep experience designing and implementing cloud solutions, preferably with Microsoft Azure. Experience with AWS or Google Cloud Platform is also valuable.

• Strong experience with Infrastructure as Code (IaC) using technologies such as Bicep, Terraform, or ARM.
• Deep understanding of Git, branching strategies, pull requests, and collaborative development practices.
• Hands-on experience with Docker and Kubernetes, including containerized application architecture and deployment.
• Experience with relational and distributed data technologies such as PostgreSQL, MySQL, Redis, and Databricks.
• Understanding of observability, application performance, logging, metrics, tracing, and security. Experience with Grafana, Azure Application Insights, or OpenTelemetry (OTel) is preferred.

Domain Expertise:

• Recent working experience in the healthcare domain, specifically with EHR and Epic technologies.
• Deep knowledge of Epic is required for integrating AI solutions., * Experience building or integrating Generative AI-powered applications.
• Epic certification is a top qualification. Preferred certifications include Clarity Data Model, Clinical Data Model, Cogito, or Caboodle Data Model.
• An advanced degree or certifications.