Job Summary
We are seeking a Lead AI Solutions Engineer with 10+ years of relevant experience to design, develop, configure, test, debug, and document cloud-based applications and AI-powered solutions. The role involves designing scalable, secure, and resilient distributed systems, implementing automated CI/CD pipelines, and leveraging Generative AI tools to improve software development productivity. The engineer will maintain end-to-end ownership of architected products, contribute to architecture and code reviews, and integrate AI solutions within Epic to support a seamless healthcare user experience.
Key Responsibilities
• Design scalable, secure, and resilient cloud applications using distributed systems, APIs, and microservices.
• Design and implement automated CI/CD pipelines using Azure DevOps, GitHub Actions, GitLab, Jenkins, or similar platforms.
• Leverage Generative AI tools to accelerate coding, testing, documentation, troubleshooting, and solution development while maintaining engineering judgment and technical ownership.
• Maintain end-to-end ownership of architected products and systems.
• Transition between high-level architecture and hands-on implementation as needed.
• Integrate AI solutions within Epic to provide a seamless user experience.
• Prepare technical design specifications and review functional requirements.
• Collaborate with development teams and participate in architecture, design, and code reviews.
• Develop and maintain operational and system-level documentation.
• Implement infrastructure provisioning and configuration using Infrastructure as Code (IaC) practices.
• Apply Git branching strategies, pull requests, code reviews, versioning, and collaborative development practices.
• Develop and deploy containerized applications using Docker and Kubernetes, considering scaling, networking, and operational requirements.
• Support application observability, performance monitoring, logging, metrics, tracing, and security.
Required Qualifications
• 10+ years of experience in a relevant technical field, with the ability to plan and accomplish complex tasks and provide technical leadership across multiple layers of resources.
• Recent hands-on experience in healthcare, specifically with Electronic Health Records (EHR) and Epic technologies.
• Deep knowledge of Epic and experience integrating AI solutions within Epic environments.
• Extensive experience designing and implementing cloud solutions, preferably using Microsoft Azure; experience with AWS or GCP is also valuable.
• Strong experience with Infrastructure as Code (IaC) and cloud provisioning using Bicep, Terraform, ARM, or equivalent tools.
• Strong software engineering fundamentals and deep understanding of Git, branching strategies, pull requests, code reviews, versioning, and collaborative development practices.
• Experience designing and implementing automated CI/CD pipelines using Azure DevOps, GitHub Actions, GitLab, Jenkins, or similar platforms.
• Hands-on experience with Docker and Kubernetes, including containerized application architecture, deployment, scaling, networking, and operational considerations.
• Experience with relational and distributed data technologies, including PostgreSQL, MySQL, Redis, and Databricks.
• Understanding of observability, application performance, logging, metrics, tracing, and security.
• Ability to leverage Generative AI tools as a productivity multiplier without compromising architectural thinking, engineering judgment, or technical ownership.
Preferred Qualifications
• Experience building or integrating Generative AI-powered applications.
• Active Epic certification, with preference for Clarity Data Model, Clinical Data Model, Cogito, or Caboodle Data Model certifications.
• Experience with Grafana, Azure Application Insights, or OpenTelemetry (OTel).
• An advanced degree or relevant certifications.
