Principal AI Engineer

OverviewCotiviti is seeking an experienced AI Engineer to design, build, and maintain a cutting-edge agentic framework and centralized AI platform that will serve as the backbone of our organization's AI initiatives. Overview Cotiviti is seeking an experienced AI Engineer to design, build, and maintain a cutting-edge agentic framework and centralized AI platform that will serve as the backbone of our organization's AI initiatives. This role will be responsible for creating a unified interface that enables teams across the company to securely deploy, manage, and access AI agents while ensuring seamless data integration and platform reliability. The role will work closely with Data Scientists, MLOps engineers, Data Engineers, and Product Engineering teams. Responsibilities Design and implement scalable agentic solutions for diverse use cases Leverage a broad stack of Open Source AI technologies to build and maintain a centralized AI platform with unified APIs for cross-functional team access and build various types of agents Work with Product Engineers to integrate AI agents into customer-facing applications and internal tools Lead technical discussions, mentor junior engineers, and help set the technical vision for the AI platform roadmap. Ensure compliance with security, privacy, and regulatory requirements across the software development lifecycle. Optimize performance of AI-powered workloads across compute and storage layers using cloud-native and open-source solutions. Conduct performance analysis and capacity planning to ensure platform scalability Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 8+ years of software engineering experience, including 2+ years working on AI/ML platforms or infrastructure. Experience in building large-scale distributed systems and microservices. Strong programming skills in Python. Hands-on experience with agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar. Experience with containerization and orchestration (e.g., Docker, Kubernetes). Understanding of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Databricks Cloud platform experience (AWS, GCP, or Azure). Originally posted on Himalayas