Senior Enterprise AI Engineer (Hybrid)

RLI Corp.; Peoria (AZ); Hybrid; USD 115,000 - 168,000; Full time

Benefits offered by this job

PTO & holidays

Hybrid work arrangements

Medical, dental and vision

ESOP

401(k) plan

Tuition reimbursement

Parental leave

Fitness subsidies

Job summary

RLI Corp is seeking a senior software engineer to design, develop, and deploy AI-enabled enterprise applications. You will build scalable cloud-native services, integrate AI capabilities with enterprise systems, and lead modernization efforts across teams.

The role emphasizes using LLMs, RAG, AI agents, and vector databases, with a strong focus on security, observability, and CI/CD automation in a hybrid work environment.

Qualifications

• Bachelor's degree in computer science or related field is required or equivalent experience.
• 7+ years of professional software engineering experience in enterprise applications.
• Experience with cloud-native architectures, distributed systems, and RESTful APIs.
• Experience with AI-enabled applications using LLMs, RAG, AI agents, and prompt engineering.

Responsibilities

• Design, develop, test, and deploy enterprise AI applications with modern software practices.
• Build AI solutions using LLMs, RAG, AI agents, and orchestration tech.
• Develop scalable backend services, REST APIs, and cloud-native apps.
• Integrate AI capabilities with enterprise systems via APIs and messaging.
• Create vector search, semantic retrieval, and knowledge-base solutions.
• Mentor teammates and contribute to CI/CD and IaC practices.

Skills

Python

Kubernetes

Docker

REST APIs

AI/ML concepts

Cloud-native

Agile

Communication

Education

Bachelor's degree in computer science or related field

Tools

GitLab

CI/CD

IaC

Job description

RLI Corp is seeking a senior software engineer to design, develop, and deploy AI-enabled enterprise applications. You will build scalable cloud-native services, integrate AI capabilities with enterprise systems, and lead modernization efforts across teams.

The role emphasizes using LLMs, RAG, AI agents, and vector databases, with a strong focus on security, observability, and CI/CD automation in a hybrid work environment.