Remote New 
Enterprise AI Engineering Architect
 MultiPlan | |
 United States | |
 Mar 26, 2026 | |
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At Claritev, we pride ourselves on being a dynamic team of innovative professionals. Our purpose is simple - we strive to bend the cost curve in healthcare for all. Our dedication to service excellence extends to all our stakeholders -- internal and external - driving us to consistently exceed expectations. We are intentionally bold, we foster innovation, we nurture accountability, we champion diversity, and empower each other to illuminate our collective potential. Be part of our amazing transformational journey as we optimize the opportunity towards becoming a leading technology, data, and innovation voice in healthcare. Onward and Upward!!! Job Summary:
At Claritev, we are revolutionizing healthcare payments through innovative solutions and data-driven insights. As the Enterprise AI Engineering Architect, you will lead the advancement of our AI engineering and infrastructure capabilities, focusing on platform reliability, scalability, and engineering excellence. You will help build and evolve the foundational AI platform--including model serving, agent frameworks, data connectivity, and secure deployment pipelines--that powers AI agents and applications across the organization.
Your role will involve driving research and development in AI engineering practices, shaping our multi-cloud/OCI architecture, and mentoring junior talent. Join us in transforming the healthcare landscape.
Job Responsibilities:
1. Utilize generative AI and engineering best practices to streamline platform services, tooling, and deployment workflows, enabling faster and more reliable development across teams.
2. Build and optimize infrastructure that supports model hosting, vector search, agent frameworks, and secure data access. 3. Drive research and development in AI platform engineering--including model serving, retrieval systems, observability, and secure AI gateway patterns--to establish reusable components and best practices. 4. Partner with AI, data science, security, and product teams to understand their needs and identify opportunities to strengthen our AI platform, improve reliability, and enable new capabilities. 5. Lead initiatives focused on developing, scaling, and hardening AI platform components such as MCP servers, vector databases, agent hosting environments, and multi-cloud model routing. 6. Ensure platform-level enforcement of ethical and responsible AI practices, including secure routing, PHI-safe processing, model observability, and compliance guardrails. 7. Mentor and develop junior AI engineers, fostering a culture of platform reliability, operational excellence, and ongoing innovation. 8. Ensure adherence to HIPAA, SOC 2, and data privacy standards across all AI infrastructure components, including logging, routing, and data storage. | |