Associate I - HR Operations

CORPORATE Job Description AI Engineer, AI Enablement | HCA Healthcare

Position Summary The AI Engineer, AI Enablement serves as a senior technical leader responsible for designing, building, and implementing enterprise-grade Agentic AI solutions aligned to HCA Healthcare’s digital and AI priorities. This role exists to translate high-value business needs into scalable, secure, and production-ready AI systems that can be integrated into enterprise platforms and workflows.

This role partners closely with product managers, data scientists, security, enterprise architecture, and engineering stakeholders to drive end-to-end technical delivery across solution architecture, development, testing, deployment, monitoring, and optimization. Success in this role requires deep hands-on AI engineering expertise, strong architectural judgment, and the ability to guide engineering best practices while providing technical leadership and mentorship across the team.

Responsibilities AI Solution Architecture & Delivery

• Lead the technical design and implementation of enterprise-grade Agentic AI solutions aligned to strategic business priorities.
• Translate business requirements into scalable, production-ready solution designs in partnership with product managers, data scientists, security, and enterprise architecture teams.
• Own the end-to-end technical delivery lifecycle, including architecture, development, testing, deployment, monitoring, and performance optimization.

AI Platform & Systems Engineering

• Design and implement scalable, secure, and reliable AI infrastructure that supports availability, performance, and adherence to enterprise privacy and regulatory standards.
• Lead architectural decisions for AI agent orchestration, tool integration, and system interoperability to ensure effective integration with existing platforms and workflows.
• Build and operationalize advanced AI solutions using modern generative AI patterns, including Retrieval-Augmented Generation architectures, vector databases, and multi-agent orchestration approaches.

Engineering Standards, Quality & Responsible AI

• Define and uphold engineering best practices for AI development, including coding standards, model evaluation methodologies, CI/CD pipelines, observability, security, and compliance requirements.
• Embed responsible and ethical AI practices into solution design through guardrails, evaluation frameworks, and human-in-the-loop considerations.
• Evaluate emerging AI technologies and frameworks and make data-driven recommendations that improve system performance, cost efficiency, scalability, and reliability.

Technical Leadership & Collaboration

• Serve as a hands-on technical leader and subject matter expert in Agentic AI, guiding complex implementations and resolving high-impact technical challenges.
• Mentor and support engineers to promote technical excellence, innovation, and continuous learning across the team.
• Stay current with advancements in AI and Agentic AI and apply relevant new techniques and tools to enhance solution capability and engineering efficiency.