Principal AI Engineer

🕒 August 12

🇺🇸 United States – Remote

💵 $208k - $260k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

Apply Now
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Cotiviti

5001 - 10000 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Cotiviti is a healthcare technology and analytics company that specializes in improving payment accuracy and performance through advanced data analytics solutions. They partner with health plans, government agencies, and healthcare providers to deliver insights that enhance quality and efficiency in care delivery. With solutions such as risk adjustment, payment policy management, and member engagement, Cotiviti aims to optimize financial and clinical outcomes for the healthcare ecosystem.

📋 Description

• Design and implement scalable agentic solutions for diverse use cases • Build and maintain a centralized AI platform using open-source AI technologies • Develop unified APIs for cross-functional team access and build various types of agents • Integrate AI agents into customer-facing applications and internal tools with Product Engineers • Lead technical discussions, mentor junior engineers, and help set the AI platform roadmap • Ensure security, privacy, and regulatory compliance across the software development lifecycle • Optimize AI-powered workloads across compute and storage layers using cloud-native and open-source solutions • Conduct performance analysis and capacity planning for platform scalability • Complete special projects and other assigned duties

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field • 12+ years of software engineering experience • 2+ years working on AI/ML platforms or infrastructure • Experience building large-scale distributed systems and microservices • Strong programming skills in Python and Java • Hands-on experience with agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar • Experience with containerization and orchestration, such as Docker and Kubernetes • Understanding of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Databricks • Cloud platform experience with AWS, GCP, or Azure • Ability to navigate complex, ambiguous, and fast-changing technologies and requirements • Ability to work independently and collaborate as a team • Ability to handle confidential information professionally • Ability to handle multiple tasks, prioritize, and meet deadlines • High-speed internet access/connectivity and office setup and maintenance • Dedicated, secure work area • Ability to perform duties with or without reasonable accommodation

🏖️ Benefits

• Discretionary bonus consideration • Medical insurance • Dental insurance • Vision insurance • Disability insurance • Life insurance coverage • 401(k) savings plan • Paid family leave • 9 paid holidays per year • 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service • Remote work arrangement • Virtual interviews • Flexible work with global and geographically dispersed US-based teams

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