Senior AI Engineer: Generative AI & LLM Systems

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

Benefits offered by this job

Annual bonus plans

ESOP/401(k) with company contributions

Paid time off

Hybrid work arrangements

Tuition reimbursement

Fitness center discounts

Job summary

RLI Corp. is seeking an experienced software engineer to design and deliver next-generation AI solutions that improve enterprise processes.

You will build intelligent applications with LLMs, RAG, AI agents, and scalable cloud-native architectures, collaborating across product, architecture, and development teams. The role emphasizes secure, maintainable AI-enabled solutions, CI/CD pipelines, and observability.

Qualifications

• Typically requires a Bachelor’s degree in computer science or a related field
• Minimum of 7 years of professional software engineering experience
• Experience with cloud-native applications and RESTful APIs
• Experience with AI-enabled applications using LLMs, RAG, and AI agents
• Experience with vector databases, embeddings, and semantic retrieval
• Proficiency with Git-based source control and CI/CD practices

Responsibilities

• Design, develop, test, and deploy enterprise AI applications with modern software practices
• Build AI solutions using LLMs, RAG, AI agents, and workflow orchestration
• Develop scalable backend services and cloud-native apps with REST APIs
• Design integrations using APIs, messaging, and event-driven architectures
• Develop document processing, OCR, and knowledge extraction solutions
• Deploy and manage apps in Kubernetes environments and mentor teammates

Skills

Python

Kubernetes

REST APIs

Cloud-native

LLMs/RAG

AI engineering

Education

Bachelor’s degree in computer science

Tools

Kubernetes

Docker

LangGraph

LangChain

Azure AI Foundry

REST APIs

Job description

RLI Corp. is seeking an experienced software engineer to design and deliver next-generation AI solutions that improve enterprise processes.

You will build intelligent applications with LLMs, RAG, AI agents, and scalable cloud-native architectures, collaborating across product, architecture, and development teams. The role emphasizes secure, maintainable AI-enabled solutions, CI/CD pipelines, and observability.