IT Sr. Analyst, AI Engineer

Patrick Industries, a publicly traded company headquartered in Elkhart, Indiana, invites you to join a team of dedicated Team Members who are passionate about delivering high-quality products and exceptional customer service. As a leading solutions provider serving a diverse range of markets across the United States, our commitment to innovation, quality, and sustainability has positioned us as a high growth, diversified and empowered Team of more than 10,000! Your adventure awaits! The IT Sr. Analyst, AI Engineer is responsible for designing, developing, deploying, and supporting enterprise AI solutions, agentic applications, and intelligent integrations across Patrick Industries. As a senior member of the Agile AI Factory, this role owns technical solution design, implementation approaches, engineering quality, and operational performance for assigned initiatives. The position partners closely with Product Managers, Platform Engineers, Data Engineers, and business stakeholders to deliver scalable AI-enabled solutions that drive automation, improve decision-making, and create measurable business value. Responsibilities & DutiesAI Solution Design & Development • Design, develop, test, and deploy AI-enabled applications, agents, and intelligent automation solutions • Own technical solution design for assigned initiatives, translating business requirements into scalable production-ready applications • Develop agentic workflows, prompt engineering strategies, retrieval-augmented generation solutions, and AI orchestration capabilities • Create reusable frameworks, services, and components that accelerate enterprise AI delivery • Develop technical documentation, design specifications, and engineering standards • Participate in code reviews, design reviews, and architecture discussions to ensure solution quality System Architecture & Engineering • Design system components, service boundaries, data flows, integration patterns, and operational workflows for assigned solutions • Evaluate architectural alternatives and make recommendations based on scalability, performance, reliability, and maintainability requirements • Assess technical trade-offs related to cost, latency, compute utilization, and solution complexity • Design solutions that support enterprise growth, operational efficiency, and long-term sustainability • Collaborate with Platform Engineers and Architects to ensure alignment with enterprise standards • Identify and proactively address technical risks, dependencies, and architectural concerns AI Platform Integration & Automation • Build integrations between AI platforms and enterprise applications, including ERP, operational systems, and business applications • Develop APIs, services, and automation frameworks that enable intelligent workflows across the organization • Support implementation of AI capabilities within manufacturing, supply chain, finance, HR, and corporate business processes • Ensure integrations are reliable, secure, scalable, and aligned with enterprise architecture standards • Troubleshoot integration challenges and optimize system performance • Collaborate with technical teams to support end-to-end solution delivery Data Engineering & AI Enablement • Build data pipelines and supporting infrastructure required for AI applications and intelligent automation • Partner with Data Engineering teams to ensure data quality, availability, governance, and readiness • Design and implement data structures that support AI model performance and business requirements • Support ingestion, transformation, and preparation of enterprise data for AI use cases • Optimize solutions for performance, scalability, and maintainability • Contribute to enterprise AI and data platform standards and best practices Solution Quality, Monitoring & Production Support • Develop and maintain testing frameworks, evaluation harnesses, and validation processes for AI solutions • Establish monitoring and observability standards for production AI systems • Track application performance, latency, error rates, model behavior, and output quality • Support deployment, stabilization, issue resolution, and ongoing production operations • Implement regression testing and validation processes when models, prompts, or retrieval layers change • Drive continuous improvement of solution reliability, performance, and supportability DevOps & Agile Delivery • Apply DevOps best practices including CI/CD pipelines, source control, automated testing, and release management • Participate in sprint planning, backlog refinement, stand-ups, reviews, and retrospectives • Collaborate with cross-functional teams to deliver prioritized work efficiently and predictably • Provide effort estimates, identify delivery risks, and communicate project status effectively • Support release planning, deployment readiness, and production rollout activities • Continuously improve engineering practices, development tools, and delivery processes Technical Leader