Senior AI Engineer

📋 Description

• • As a Senior AI Engineer at BlueCross BlueShield of Tennessee, you will be at the forefront of developing and deploying sophisticated AI solutions designed to enhance member-facing virtual assistants. Your primary mission will be to ensure our AI assistant provides accurate, personalized, and reliable information at scale, directly impacting the member experience and operational efficiency.
• • This role is inherently collaborative, requiring you to work closely with cross-functional teams including product managers, software engineers, data scientists, and business stakeholders. You will be instrumental in identifying high-value integration opportunities, establishing clear data contracts, and defining service expectations to streamline the delivery of AI-powered features.
• • A key responsibility will be connecting the AI assistant to critical internal and external APIs and structured data sources. This involves not only implementing these connections but also driving the adoption of robust quality and reliability practices, such as comprehensive testing, proactive monitoring, and effective incident prevention strategies. Your efforts will be crucial in building trust with our members and ensuring confidence among internal partners.
• • You will architect, design, and implement complex, state-of-the-art AI models and algorithms, with a strong emphasis on leveraging Python and cloud platforms, particularly GCP Vertex AI. This includes developing and optimizing machine learning and deep learning models, potentially including Large Language Models (LLMs) and diffusion models, to address specific healthcare payer use cases.
• • You will play a pivotal role in the entire lifecycle of AI solutions, from ideation and development through to productionalization. This involves translating complex business needs and technical requirements into actionable AI strategies and implementations that drive tangible business value and process automation.
• • Conduct in-depth research into the latest advancements in Artificial Intelligence and Machine Learning. You will be expected to maintain a high level of expertise, championing the adoption of cutting-edge techniques and methodologies within the engineering team and across the organization.
• • Design and develop robust, scalable, and efficient systems and codebases for deploying AI models into production environments. This requires a strong understanding of MLOps principles to ensure high availability, performance, and maintainability of AI services.
• • Act as a key technical advisor to internal Lines-of-Business, deeply understanding their complex needs, gathering detailed requirements, and translating them into impactful AI solutions that solve critical business challenges.
• • Define, implement, and oversee evaluation and validation frameworks for AI models. This ensures that models meet stringent requirements for accuracy, reliability, fairness, and overall performance, exceeding business expectations.
• • Mentor and guide junior engineers, fostering a culture of technical excellence. You will share best practices in AI development, model implementation, system design, and MLOps, contributing to the growth and development of the team.
• • You will be responsible for leading technically challenging projects from conception through to deployment, demonstrating strong technical leadership and project management skills.
• • Effectively interpret and translate complex technical concepts into clear, concise information that is meaningful to project team members, business personnel, and leadership, facilitating informed decision-making.
• • Contribute to the strategic thinking and planning for AI initiatives within the company, identifying new opportunities and driving innovation.
• • Ensure the secure and compliant integration of AI systems with sensitive healthcare data, adhering to all relevant regulations and company policies.
• • Drive continuous improvement in AI model performance and operational efficiency through ongoing monitoring, analysis, and iterative development.
• • Collaborate with data engineers and platform teams to ensure data pipelines are optimized for AI model training and inference.
• • Develop and maintain comprehensive documentation for AI models, systems, and processes.
• • Participate in code reviews and architectural discussions to ensure the quality and maintainability of AI solutions.
• • Stay abreast of industry trends, emerging technologies, and best practices in AI and machine learning, particularly within the healthcare domain.
• • Contribute to building a strong AI engineering practice within BlueCross BlueShield of Tennessee.