Hybrid Principal AI Engineer

at Humana

• Job title: Principal AI Engineer
• Job type: Full Time
• Experience level: Lead
• Salary: $172,200 - $236,900 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Docker, Flask, Google Cloud Platform, GRPC, Kubernetes, Python
• Location requirements: Hybrid, Louisville, United States

About the role

• Principal AI Engineer at Humana focused on enterprise platform strategy and AI systems design. Leading development of agentic AI platforms and influencing architectural direction.

Responsibilities

• Serves as a senior technical authority responsible for guiding Humana’s enterprise platform strategy and engineering execution
• Leads the design, development, and operation of foundational agentic AI platforms, tools, and services that empower development teams to build, deploy, and operate agent-driven applications efficiently, securely, and reliably
• Influences architectural direction for core infrastructure supporting agentic AI workloads
• Drives innovation in developer experience and automation—including agent orchestration and human-AI collaboration
• Mentors engineering teams, ensuring that platform solutions are robust, scalable, secure, and aligned with Humana’s enterprise agentic AI technology roadmap
• Evaluates, selects, and integrates foundational agentic AI technologies
• Builds and maintains robust CI/CD and agentic AI pipeline automation for automated testing, deployment, and release management
• Develops internal tools, APIs, and services that abstract agentic AI infrastructure complexity

Requirements

• 10+ years of total engineering experience
• Bachelor’s or Master’s in Computer Science, Engineering, or a related quantitative field
• 10+ years of professional software or platform engineering experience
• Deep expertise in Python, including building production services and shared libraries used by others
• Hands-on experience with modern AI systems, including LLM integration, RAG, embeddings, and applied generative AI patterns
• Strong background in machine learning engineering, including model deployment, monitoring, evaluation, and lifecycle management
• Expert-level understanding of FastAPI, Flask, or similar frameworks, and REST/gRPC service design
• Strong proficiency with cloud-native development on AWS, GCP, or Azure
• Minimum 5 years of containerization and orchestration experience (Docker, Kubernetes)
• Production experience with CI/CD pipelines, version control, and modern DevOps practices
• Demonstrated ability to own large, ambiguous problems and deliver high-value, high-quality solutions

Benefits

• medical, dental and vision benefits
• 401(k) retirement savings plan
• time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave)
• short-term and long-term disability
• life insurance and many other opportunities