Experienced AI Engineer - Generative AI/Machine Learning

rlicorp; Peoria (AZ); On-site; USD 150,000 - 210,000; Full time

Job summary

RLI Corp seeks an accomplishedSenior AI Software Engineer to design, develop, and deploy AI-enabled enterprise applications. You will build scalable backend services, REST APIs, and cloud-native solutions that integrate AI capabilities with enterprise systems.

Responsibilities include implementing LLM-based workflows, vector search, and knowledge ingestion, while collaborating with product owners and engineers to deliver robust, secure, and maintainable AI solutions.

Qualifications

• 7+ years of professional software engineering experience
• Experience designing cloud-native distributed systems
• Experience with AI-enabled applications using LLMs and RAG
• Experience with vector databases, embeddings, and semantic retrieval
• Experience with API design, microservices, and event-driven architectures

Responsibilities

• Design, develop, test, and deploy enterprise AI applications
• Build AI-enabled solutions using LLMs, RAG, and AI agents
• Develop scalable backend services and REST APIs
• Integrate enterprise systems via APIs, messaging, and event-driven patterns
• Create vector search, semantic retrieval, and knowledge ingestion pipelines
• Deploy and manage applications in Kubernetes environments
• Collaborate with stakeholders to translate business needs into AI-enabled solutions
• Participate in architecture reviews, code reviews, Agile ceremonies, and CI/CD pipelines
• Mentor team members and promote code quality, security, and observability

Skills

Python

Cloud-native

LLMs

Vector search

REST APIs

Kubernetes

CI/CD

Agile

Education

Bachelor's degree in computer science or related field

Tools

Git

GitLab

Docker

Kubernetes

Job description

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.

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 vector search, semantic retrieval, embeddings, and knowledge ingestion pipelines for enterprise AI solutions.
• Knowledge of intelligent document processing technologies including OCR, document processing pipelines, and structured and unstructured document extraction.
• Experience integrating enterprise systems using APIs, messaging, and event-driven architectures.
• Knowledge of DevOps tools and practices including Git, GitLab, GitLab CI/CD, Infrastructure as Code (IaC), and automated deployment pipelines.
• Ability to leverage AI-assisted development tools while maintaining high standards for software quality, security, testing, and ob