Lead AI Engineer

Elevance Health • Mason, OH

1d • Hybrid

About The Position

Lead AI Engineer Location: This role requires associates to be in-office 3 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Alternate locations may be considered if candidates reside within commuting distance from an office Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law. PLEASE NOTE: This position is not eligible for current or future visa sponsorship The Lead AI Engineer will drive the design, development, and deployment of AI solutions in healthcare. This role focuses on building production-grade, compliant, and trustworthy AI systems that improve healthcare outcomes, operational efficiency, and decision-making. You will lead AI initiatives end-to-end while working closely with clinical, product, data, and engineering teams in a highly regulated environment. How You Will Make an Impact: Lead the architecture and implementation of AI and Agentic AI solutions for healthcare use cases. Design scalable, secure, and compliant AI systems aligned with healthcare regulations. Establish standards for model governance, validation, monitoring, and explainability. May implement improvements in stability, performance, and scalability across major business-critical systems. May implement processes to reduce barriers and roadblocks in projects, services, and processes in order to operate more efficiently. Build, train, and deploy ML and deep learning models using healthcare data (claims, EHR, clinical notes, imaging, etc.). Develop data pipelines for structured and unstructured healthcare data. Implement APIs and services to serve AI models in production environments. Apply and evaluate Generative AI and LLMs for healthcare use cases (clinical summarization, coding support, member engagement, operational automation). Develops and defines application scope and objectives and supervises the preparation of technical and/or functional specifications from with programs will be written. Performs technical design reviews and code reviews. Ensure AI solutions meet HIPAA, PHI, and data privacy requirements. Implement responsible AI practices including bias detection, fairness evaluation, and explainability. Collaborate with legal, compliance, and security teams on model governance. Partner with product managers, clinicians, data scientists, and business stakeholders to translate healthcare needs into AI solutions. Identify high-impact healthcare AI use cases and guide prioritization. Communicate complex AI concepts clearly to clinical and non-technical audiences. Owns the technical development environment and works on the Enterprise team. Leads multiple or large projects and facilitates large group JAD sessions for requirements, modeling in several disciplines. Mentor and guide AI engineers in best practices and healthcare-specific considerations. Review code, models, and architectures. Contribute to hiring, onboarding, and building a high-performing AI team.

Requirements

• Requires an BA/BS degree in Information Technology, Computer Science or related field of study and a minimum of 7 years related experience; multi-platform, multi-dimensional experience, and expert level experience with business and technical applications; or any combination of education and experience, which would provide an equivalent background.

Nice To Haves

• 7+ years of software engineering experience, with 4+ years in AI/ML roles.
• Strong expertise in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).
• Proven experience deploying AI/ML models into production healthcare environments.
• Solid understanding of: Machine learning and deep learning techniques. Model evaluation, validation, and monitoring. Data pipelines and feature engineering.
• Experience with cloud platforms (AWS, Azure), including secure data handling.
• Familiarity with MLOps practices (CI/CD, model versioning, drift detection).
• Strong understanding of data privacy and security principles.

Responsibilities

• Lead the architecture and implementation of AI and Agentic AI solutions for healthcare use cases.
• Design scalable, secure, and compliant AI systems aligned with healthcare regulations.
• Establish standards for model governance, validation, monitoring, and explainability.
• May implement improvements in stability, performance, and scalability across major business-critical systems.
• May implement processes to reduce barriers and roadblocks in projects, services, and processes in order to operate more efficiently.
• Build, train, and deploy ML and deep learning models using healthcare data (claims, EHR, clinical notes, imaging, etc.).
• Develop data pipelines for structured and unstructured healthcare data.
• Implement APIs and services to serve AI models in production environments.
• Apply and evaluate Generative AI and LLMs for healthcare use cases (clinical summarization, coding support, member engagement, operational automation).
• Develops and defines application scope and objectives and supervises the preparation of technical and/or functional specifications from with programs will be written.
• Performs technical design reviews and code reviews.
• Ensure AI solutions meet HIPAA, PHI, and data privacy requirements.
• Implement responsible AI practices including bias detection, fairness evaluation, and explainability.
• Collaborate with legal, compliance, and security teams on model governance.
• Partner with product managers, clinicians, data scientists, and business stakeholders to translate healthcare needs into AI solutions.
• Identify high-impact healthcare AI use cases and guide prioritization.
• Communicate complex AI concepts clearly to clinical and non-technical audiences.
• Owns the technical development environment and works on the Enterprise team.
• Leads multiple or large projects and facilitates large group JAD sessions for requirements, modeling in several disciplines.
• Mentor and guide AI engineers in best practices and healthcare-specific considerations.
• Review code, models, and architectures.
• Contribute to hiring, onboarding, and building a high-performing AI team.

Benefits

• We offer a range of market-competitive total rewards that include merit increases, paid holidays, Paid Time Off, and incentive bonus programs (unless covered by a collective bargaining agreement), medical, dental, vision, short and long term disability benefits, 401(k) +match, stock purchase plan, life insurance, wellness programs and financial education resources, to name a few.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees