Senior AI Engineer for Enterprise AI & Automation

Patrick Industries

Elkhart (IN)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

401K match

Paid vacation

Tuition reimbursement

Job summary

Patrick Industries, headquartered in Elkhart, Indiana, seeks an IT Sr. Analyst, AI Engineer to design, develop, deploy, and support enterprise AI solutions, agentic applications, and intelligent integrations across the organization.

You will partner with Product Managers, Platform Engineers, Data Engineers, and stakeholders to deliver scalable AI-enabled solutions that drive automation and business value. The role focuses on system architecture, data flows, APIs, and production readiness within

Qualifications

Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or related field; equivalent experience may be considered.
4+ years of software engineering, AI engineering, data engineering, or related experience.
Experience designing, developing, and deploying enterprise software applications and integrations.
Hands-on experience building and implementing AI, machine learning, generative AI, or agentic solutions.
Experience with prompt engineering, retrieval-augmented generation, LLM orchestration, and AI development frameworks.
Demonstrated system design and software architecture experience.
Experience developing APIs, integrations, and distributed application components.
Strong understanding of DevOps practices including CI/CD, source control, automated testing, and release management.
Familiarity with Microsoft Azure, Microsoft Fabric, Microsoft Foundry, Azure DevOps, and Dynamics 365 environments.
Knowledge of monitoring, observability, and production support practices for enterprise applications.
Experience with MLOps, model deployment, monitoring, and lifecycle management preferred.
Experience supporting manufacturing, operations, supply chain, or industrial business environments preferred.
Experience integrating enterprise applications, industrial systems, sensors, or operational technologies preferred.
Experience in decentralized, multi-site, or acquisition-driven organizations preferred.
Exposure to C#, Rust, or KQL is a plus.
Strong analytical, communication, collaboration, and problem-solving skills.

Responsibilities

Design, develop, test, and deploy AI-enabled applications and agents.
Own technical solution design for 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.
Design system components, data flows, integration patterns, and operational workflows for assigned solutions.
Evaluate architectural alternatives based on scalability, performance, reliability, and maintainability.
Build integrations between AI platforms and enterprise applications, including ERP and operational systems.
Develop APIs, services, and automation frameworks that enable intelligent workflows.
Support implementation of AI capabilities within manufacturing, supply chain, finance, HR, and corporate processes.
Ensure integrations are secure, scalable, and aligned with enterprise architecture standards.
Troubleshoot integration challenges and optimize system performance.
Collaborate 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.