Senior AI Platform Lead & Architect

Humana, Inc.; United States; Hybrid; USD 129,000 - 178,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

401(k) retirement savings

Paid time off

Disability insurance

Life insurance

Job summary

Humana, Inc. is seeking a Lead AI Software Engineer to drive the design, development, and scaling of production-grade AI solutions in a hybrid, enterprise environment.

You will lead architectural decisions, mentor engineers, and collaborate with platform, infrastructure, and DevOps teams to ensure scalable, reliable, and cost-efficient AI systems using LLMs and modern cloud-native tech.

Qualifications

• 8+ years of software engineering with demonstrated technical leadership.
• Proven experience building and delivering large-scale, production-grade software platforms.
• Strong backend development expertise with Python, Java, or similar languages.
• Experience designing distributed systems and cloud-native applications.
• Demonstrated ability to lead technical initiatives from architecture through deployment.
• Experience working in agile environments with frequent delivery and iteration.

Responsibilities

• Provide technical leadership and architectural direction for strategic AI initiatives.
• Design scalable, cloud-native AI platforms and services.
• Lead design and code reviews and establish engineering standards.
• Develop end-to-end AI solutions including APIs, data pipelines, and orchestration layers.
• Mentor software engineers and data scientists to raise engineering maturity.

Skills

Technical leadership

Cloud architecture

Python/Java

Distributed systems

Agile delivery

Mentoring

Communication

Education

Bachelor’s degree in Engineering/Data Science

Tools

GCP

AWS

Azure

Kubernetes

APIs/Microservices

Job description

Humana, Inc. is seeking a Lead AI Software Engineer to drive the design, development, and scaling of production-grade AI solutions in a hybrid, enterprise environment.

You will lead architectural decisions, mentor engineers, and collaborate with platform, infrastructure, and DevOps teams to ensure scalable, reliable, and cost-efficient AI systems using LLMs and modern cloud-native tech.