BlueCross BlueShield of Tennessee
BlueCross BlueShield of Tennessee
BlueCross BlueShield of Tennessee is a Tennessee-based health plan provider serving 3.4 million members through its work in healthcare and insurance. As an independent licensee of the Blue Cross Blue Shield Association and a qualified Health Insurance Marketplace issuer, the company combines health coverage with customer service and community-focused care. Its careers span a range of professional opportunities, including the BlueBridge internship program, which helps students and recent graduates begin their careers. BlueCross BlueShield of Tennessee also emphasizes a workplace where employees are valued, respected, and included.

Senior AI Engineer (Hybrid) - Chattanooga, TN

Lead the development of AI platforms, MCP services, and enterprise integrations for healthcare payer applications at BlueCross BlueShield of Tennessee. Own production AI delivery, model deployment, evaluation, and automation initiatives.

Description

  • Lead the concept development, delivery, and production launch of advanced AI solutions for healthcare payer applications
  • Design and implement sophisticated AI models and algorithms with Python and cloud services including GCP Vertex AI
  • Work with product teams and business stakeholders to prioritize AI opportunities that address operational challenges and automate processes
  • Track developments in artificial intelligence and promote the practical adoption of emerging methods
  • Build scalable, efficient architectures and codebases for deploying machine learning models in production
  • Advise internal business units by gathering requirements and converting them into effective AI solutions
  • Create and manage evaluation and validation practices covering model accuracy, reliability, fairness, and performance
  • Coach junior engineers in AI development, model implementation, and system architecture
  • Build the AI integration and automation foundation for Core Payer Applications
  • Deliver AI platform features, MCP services, and enterprise integrations that connect AI agents to applications, APIs, and data sources

Requirements

  • Bachelor’s degree in STEM or a related discipline, or equivalent professional experience
  • At least five years of relevant experience in analytics, technology, software engineering, healthcare, or a comparable field
  • At least three years of practical experience with machine learning, deep learning, and preferably AI models
  • Background designing and developing enterprise integrations, APIs, or platform services in regulated settings
  • Experience with AI agents, MCP (Model Context Protocol), tool calling, or comparable frameworks
  • Ability to convert business workflows into scalable solutions enhanced by artificial intelligence
  • Experience working with large, complex datasets to develop and optimize advanced data science pipelines
  • Strong knowledge of machine learning and deep learning frameworks such as PyTorch and TensorFlow, natural language processing, and libraries including Hugging Face Transformers
  • Experience deploying and operating machine learning models in cloud environments; GCP Vertex AI is preferred, with AWS SageMaker or Azure ML also accepted
  • Advanced proficiency in Python and relevant data science and machine learning libraries
  • Proficiency with Microsoft Office applications, including Outlook, Word, Excel, and PowerPoint
  • Ability to architect, design, and deliver complex technical systems
  • Record of leading technically demanding initiatives from initial concept through deployment
  • Ability to explain complex technical concepts clearly to project teams, business staff, and leadership
  • Capability to provide technical direction and mentorship
  • Strong communication and influencing skills with technical and non-technical colleagues and stakeholders
  • Visa sponsorship is not available for this position
  • Final-round interviews must be conducted at the Chattanooga, Tennessee headquarters

Benefits

  • Employee worker classification
  • Equal employment opportunity protections
  • Fully remote work arrangement
  • Mission-focused work supporting improved health outcomes

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