About Us 

We’re not like other insurance companies. From our specialty products to our business model, our culture to our results — we’re different. Different is who we are, and how we work, interact, deliver and succeed together. Creating a different and better insurance experience doesn’t just happen. It takes focus and a shared passion for going beyond the expected to forge relationships and deliver care that makes a difference. This approach rises from and is supported by our talented, ethical and smart team of employee owners united around a single purpose: to work alongside our customers and partners when they need us, in unexpected ways, with exceptional results. Apply today to make a difference with us. 

RLI is a Glassdoor Best Places to Work company with a strong, successful background. For decades, our financial track record has been stellar — a testament to our culture and validation of our reputation as an excellent underwriting company.

Position Purpose

Under general management, design, develop, and deliver next-generation AI solutions that improve business processes across the enterprise. Develop intelligent applications, integrate AI capabilities with enterprise systems, and build scalable cloud-native solutions that enable automation, knowledge discovery, and operational efficiency. Collaborate with product owners, architects, business stakeholders, and development teams to design secure, scalable, and maintainable AI-enabled solutions that solve complex business challenges.

Principal Duties & Responsibilities

• Design, develop, test, and deploy enterprise AI applications using modern software engineering practices.
• Build intelligent solutions utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and workflow orchestration technologies.
• Develop scalable backend services, REST APIs, and cloud-native applications that integrate AI capabilities with enterprise systems.
• Design and implement integrations using APIs, messaging, and event-driven architectures.
• Develop document processing, OCR, and knowledge extraction solutions using AI technologies.
• Design and implement vector search, semantic retrieval, and enterprise knowledge base solutions.
• Deploy, manage, and optimize applications within Kubernetes-based environments.
• Collaborate with business partners to understand business needs and translate them into practical AI-enabled solutions.
• Participate in architecture reviews, code reviews, Agile ceremonies, technical planning, and solution design discussions.
• Contribute to CI/CD pipelines, infrastructure automation, and software engineering best practices.
• Mentor team members and promote high standards for software quality, testing, security, observability, and maintainability.
• Assist with special projects or perform other duties as assigned.

Education & Experience

• Typically requires a Bachelor’s degree in computer science or a related field
• Minimum of 7 years of professional software engineering experience designing, developing, and supporting enterprise applications.
  • Equivalent combination of education and experience will be considered.
• Experience designing and developing cloud-native applications, distributed systems, and RESTful APIs.
• Experience developing AI-enabled applications utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agent frameworks, and prompt engineering techniques.
• Experience designing and implementing vector databases, vector search, embeddings, and semantic retrieval solutions.
• Experience using AI-assisted software development tools to improve software design, development, testing, and delivery.
• Experience working within Agile software development environments utilizing Git-based source control and CI/CD practices.

Knowledge, Skills, & Competencies

• Strong proficiency in Python and modern software engineering principles.
• Strong understanding of software architecture, object-oriented design, and design patterns.
• Ability to design and develop scalable cloud-native applications utilizing Kubernetes, Docker, REST APIs, and microservices.
• Knowledge of modern AI application architecture including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, LangGraph, LangChain, Azure AI Foundry, prompt engineering, and AI model evaluation.
• Ability to design and implement vec