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Senior AI Engineer (remote)

MultiPlan
United States, New York, New York
7900 Tysons One Place (Show on map)
Aug 28, 2025

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:

Claritev is revolutionizing healthcare payments through innovative solutions and data-driven insights. As the Senior AI Engineer, you will lead the advancement of our AI capabilities, focusing on engineering excellence and leveraging generative AI to enhance our end-to-end operations from experimentation to deployment. Your role will involve driving research and development in analytical techniques, creating new AI-driven products, and mentoring junior talent. Join us in transforming the healthcare landscape!

JOB ROLES AND RESPONSIBILITIES:

  • Enhance AI Operations:

    • Utilize generative AI to streamline processes and tools, enabling faster and more effective development and deployment.
    • Build scalable GenAI infrastructure with Terraform, Docker, Helm, and Kubernetes (OKE, AKS).
    • Architect hybrid AI systems across OCI, Azure, and on-prem GPU clusters.
    • Automate model pipelines (training fine-tuning inference) using Jenkins, GitHub Actions, and MLflow
      - Serve multimodal LLMs with vLLM, Triton, and Streamlit dashboards.
    • Deploy secure RAG-based microservices backed by Vector DBs, Databricks, and private LLM gateways


  • Lead R&D Efforts: Drive research and development using generative AI to create reusable code components and establish best practices.
  • Stakeholder Collaboration: Partner with stakeholders to identify opportunities for new AI-driven products through data insights.
  • Program-Level Initiatives: Lead initiatives focused on the initial development of AI-powered products.
  • Ethical AI/ML Practices: Ensure AI models are transparent, relevant, and ethically used.
  • Team Management: Mentor and develop junior data scientists, fostering a culture of continuous learning and innovation.
  • Compliance: Ensure adherence to HIPAA regulations and data privacy standards: HIPAA, SOC2, BAA enforcement, PHI-safe model routing.

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