The IT Analyst, AI Engineer is responsible for designing, building, testing, deploying, and supporting AI-enabled applications, integrations, and agentic solutions across Patrick Industries. As a hands-on engineering role within the Agile AI Factory, this position develops production-ready AI capabilities that automate business processes, enhance decision-making, and integrate AI technologies with enterprise systems. The AI Engineer partners closely with product managers, platform engineers, data engineers, and business stakeholders to deliver scalable, secure, and reliable AI solutions that support enterprise objectives.
Responsibilities & Duties:AI Solution Development
- Design, develop, test, and deploy AI-enabled applications, agents, and automation solutions
- Build production-ready software components that support enterprise AI initiatives
- Implement AI workflows, agent orchestration, prompt engineering, and retrieval-augmented generation capabilities
- Translate business and technical requirements into scalable software solutions
- Develop reusable components and integration patterns that accelerate future AI delivery
- Create and maintain technical documentation for solutions, integrations, and development standards
Application & Systems Integration
- Build integrations between AI platforms and enterprise systems, including ERP, business applications, and operational technologies
- Develop APIs, services, and integration layers that enable secure and reliable information exchange
- Support connectivity between AI solutions, data platforms, and business applications
- Troubleshoot integration issues impacting delivery, performance, and production stability
- Ensure integrations align with enterprise architecture and security standards
- Collaborate with business and technical teams to support end-to-end solution delivery
Data Engineering & AI Enablement
- Develop data pipelines and supporting infrastructure required for AI applications and workflows
- Partner with Data Engineering teams to ensure data quality, availability, and readiness
- Support ingestion, transformation, and preparation of data for AI and analytics use cases
- Design solutions that optimize data accuracy, performance, and scalability
- Assist with implementation of enterprise AI and data platform standards
- Support AI model utilization through reliable data architecture and engineering practices
Solution Quality, Testing & Monitoring
- Develop and maintain test cases, evaluation criteria, and regression testing processes for AI solutions
- Validate AI outputs and ensure solution quality meets business and technical requirements
- Implement monitoring and observability standards for AI applications, workflows, and integrations
- Monitor latency, performance, reliability, and output quality in production environments
- Support issue resolution, defect remediation, and ongoing production support activities
- Continuously improve solution stability and operational performance
DevOps & Agile Delivery
- Apply DevOps best practices including CI/CD, source control, automated testing, and release management
- Participate in sprint planning, backlog refinement, stand-ups, reviews, and retrospectives
- Collaborate with cross-functional delivery teams to execute prioritized work
- Provide effort estimates, status updates, and risk identification for assigned initiatives
- Support deployment planning, release execution, and production readiness activities
- Follow enterprise governance, security, and responsible AI standards throughout development
Engineering Design & Technical Contribution
- Contribute to solution architecture discussions and engineering design decisions within assigned projects
- Identify and communicate technical trade-offs related to cost, scalability, performance, reliability, and maintainability
- Evaluate technical feasibility and support development of implementation approaches
- Escalate architectural concerns and solution risks when appropriate
- Recommend improvements to development standards, tools, and engineering practices
- Stay current on emerging AI technologies, frameworks, and software engineering techniques
AI Initiative Execution
- Deliver technology solutions that support enterprise AI priorities and business transformation efforts
- Contribute to automation, intelligent workflow, analytics, and AI-enabled business initiatives
- Support development of capabilities across operations, supply chain, manufacturing, finance, and corporate functions
- Assist with measurement and monitoring of solution adoption and business impact
- Collaborate with Product Managers and business stakeholders to ensure delivered solutions achieve intended outcomes
Qualifications and Skills:- Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or related field; equivalent experience may be considered
- 2+ years of software engineering, data engineering, AI engineering, or related experience
- Experience designing, building, testing, and supporting software applications and integrations
- Experience with AI, machine learning, generative AI, agent-based systems, or intelligent automation solutions
- Proficiency with Python, SQL, and JavaScript/TypeScript or similar development languages
- Knowledge of prompt engineering, AI orchestration frameworks, and retrieval-augmented generation concepts
- Experience with APIs, system integrations, and enterprise application connectivity
- Experience with version control systems, automated testing, and CI/CD practices
- Familiarity with Agile development methodologies including Scrum and Kanban
- Understanding of software architecture, system design, and engineering best practices
- Experience with Microsoft Azure, Microsoft Fabric, Microsoft Foundry, Azure DevOps, and Dynamics 365 environments preferred
- Familiarity with monitoring, observability, and application performance management concepts
- Experience integrating AI solutions with enterprise systems and business processes preferred
- Exposure to manufacturing, operations, supply chain, or industrial environments preferred
- Experience in decentralized, multi-site, or acquisition-driven organizations preferred
- Familiarity with MLOps, model deployment, monitoring, and lifecycle management is a plus
- Exposure to C#, Rust, or KQL is a plus
- Strong analytical, problem-solving, communication, and collaboration skills
Benefits Include:Health, Dental, Vision, Life, Insurances, Paid Vacation, 401K Match, Holidays, Health Club and Tuition Reimbursement
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