Senior AI Engineer

BlueCross BlueShield of Tennessee•Chattanooga, TN

1d•Remote

About The Position

BlueCross BlueShield of Tennessee is seeking a Senior AI Engineer to lead the design, development, deployment, and support of advanced AI solutions across the healthcare payer ecosystem. As part of the MLOps team, this position operates at the intersection of AI engineering, MLOps, and applied business problem-solving. The Senior AI Engineer will help evaluate and adopt emerging AI platforms, shape how AI solutions are architected and delivered, and collaborate with cross-functional teams to bring production-ready solutions to life. This role also plays a key part in mentoring engineers and establishing best practices for modern AI development. Why This Role Is Exciting: End-to-End Impact — Work across the full lifecycle, from use case discovery and prototyping to delivering enterprise-scale AI solutions Hybrid AI Role — Engage across AI engineering, Generative AI, and MLOps in a single, high-impact position Modern Technology Exposure — Work hands-on with LLMs, evaluation frameworks, observability tools, and cloud-native platforms Cross-Functional Collaboration — Partner with business and technical stakeholders to solve real-world challenges Influence & Ownership — Help define standards, delivery models, and enterprise AI architecture Culture of Innovation — Thrive in an environment that encourages continuous learning, experimentation, and collaborative ideation Note: This is a fully remote role, but final interviews at our Chattanooga, TN headquarters will be required. Sponsorship is available for this role.

Requirements

Bachelor's degree in STEM (Science, Technology, Engineering or Math) or related field or equivalent work experience required.
5+ years of relevant work experience in analytics, technology, software engineering, or healthcare (academic experience included), or related equivalent experience.
3+ years of hands-on experience specifically with machine learning, deep learning, and preferably AI models (e.g., LLMs, diffusion models) is required.
Proven experience handling large, complex datasets to build and optimize sophisticated data science pipelines.
Deep experience with Machine Learning, Deep Learning frameworks (e.g., Pytorch, TensorFlow), Natural Language Processing (NLP), and associated libraries (e.g., Hugging Face Transformers).
Experience deploying and managing ML models in cloud environments (GCP Vertex AI preferred, AWS SageMaker or Azure ML acceptable).
Expert proficiency in Python and relevant data science/ML libraries.
Proficient in Microsoft Office (Outlook, Word, Excel, and PowerPoint).
Proven ability to architect, design, and implement complex systems.
Demonstrated success leading technically challenging projects from conception through to deployment.
Exceptional ability to interpret and translate complex technical concepts into information meaningful to project team members, business personnel and leadership.
Strong technical leadership and mentorship capabilities.
Must be able to communicate effectively and influence both technical and non-technical co-workers and stakeholders.
Highly organized, reliable, capable of managing multiple complex tasks, demonstrating an exceptional work ethic and strategic thinking.

Nice To Haves

Master’s or PhD degree in a relevant field (e.g., Computer Science, AI, Machine Learning) strongly preferred.

Responsibilities

Lead the ideation, development, and productionalization of sophisticated AI solutions tailored for healthcare payer use cases.
Architect, design, and implement complex, state-of-the-art AI models and algorithms, leveraging Python and cloud platforms like GCP Vertex AI.
Partner strategically with product teams and business stakeholders to define and prioritize opportunities for applying advanced AI techniques to solve critical business challenges and drive process automation.
Conduct in-depth research and maintain expertise in the latest advancements in AI, championing the adoption of cutting-edge techniques and methodologies within the team.
Architect and develop robust, scalable, and efficient systems and code bases for deploying AI models into production environments, ensuring high availability and performance.
Serve as a key technical advisor to our internal Lines-of-Businesses, understanding complex needs, gathering requirements, and translating them into impactful, actionable AI solutions.
Define and oversee the evaluation and validation frameworks for AI models, ensuring their accuracy, reliability, fairness, and performance exceed business requirements.
Mentor and guide junior engineers on best practices in AI development, model implementation, and system design.