Manager, AI Engineering

Rockwell Automation•Milwaukee, WI

2d•Hybrid

About The Position

Rockwell Automation is seeking a Manager, AI Engineering within the Integrated Supply Chain (ISC) AI Center of Excellence. This role will lead a team of AI Engineers responsible for architecting, building, deploying, and sustaining production-grade AI solutions across global supply chain operations. The Manager, AI Engineering will own the technical engineering capability for ISC AI. This includes solution architecture, engineering standards, GenAI application development, reusable technical patterns, integration design, production reliability, and sustainment. This leader will work closely with AI Delivery, IT, Analytics, Cybersecurity, Data Governance, and business stakeholders to convert prioritized use cases into secure, scalable, maintainable AI solutions.

Requirements

Bachelor's Degree or Equivalent Years of Relevant Work Experience.
Legal authorization to work in the U.S. We will not sponsor individuals for employment visas, now or in the future, for this job opening.

Nice To Haves

Typically requires a minimum of 5 years management experience.
Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, or equivalent practical experience.
10+ years of experience in software engineering, AI engineering, ML engineering, data engineering, cloud engineering, or related technical roles.
5+ years of experience leading technical teams, engineering programs, or complex technology delivery in a matrixed enterprise environment.
Strong technical background in Python, APIs, cloud-native development, data integration, automation, and production software engineering.
Experience designing, deploying, and supporting AI, ML, GenAI, LLM, automation, or advanced analytics solutions in production environments.
Experience with DevOps, CI/CD, automated testing, monitoring, observability, versioning, release management, and operational support.
Ability to explain technical tradeoffs, risks, architecture decisions, and implementation options to technical and business stakeholders.
Experience building GenAI applications using RAG, vector databases, embeddings, prompt orchestration, agentic workflows, model evaluation, and retrieval quality testing.
Experience with Microsoft Azure AI services, Azure OpenAI, Azure DevOps, GitHub Actions, containerization, serverless architectures, APIs, and enterprise cloud deployment patterns.
Experience integrating AI solutions with Microsoft 365, SharePoint, Graph API, Power Platform, enterprise data platforms, workflow automation tools, and business applications.
Experience establishing reusable AI engineering frameworks, reference architectures, prompt/model evaluation methods, and production support models.
Experience in manufacturing, supply chain, procurement, planning, logistics, quality, operations, or industrial environments.
Familiarity with responsible AI, cybersecurity, identity and access management, data privacy, auditability, model risk, and enterprise AI governance.
Advanced degree or certifications in cloud, AI/ML, software engineering, cybersecurity, data engineering, architecture, or related fields.

Responsibilities

Lead the ISC AI engineering function, including technical architecture, engineering standards, development practices, reusable patterns, and production support expectations.
Define solution approaches for GenAI applications, LLMs, RAG pipelines, prompt orchestration, agent-based workflows, document intelligence, knowledge assistants, and process automation.
Ensure AI solutions align with enterprise architecture, Azure AI platform standards, cybersecurity requirements, responsible AI expectations, and ISC data governance requirements.
Lead, coach, and develop a team of AI Engineers responsible for building and supporting production-grade AI solutions across global supply chain use cases.
Establish engineering practices for code quality, documentation, version control, testing, prompt management, evaluation, deployment, monitoring, and support.
Build team capability in Python, APIs, Azure AI, LLM application development, RAG, vector databases, data integration, workflow automation, and enterprise software delivery.
Oversee the design and development of AI applications, including RAG-based assistants, agentic workflows, document processing, workflow automation, and AI-enabled business applications.
Guide model, framework, and tool selection based on accuracy, latency, cost, scalability, security, compliance, and maintainability.
Ensure AI solutions integrate with governed data sources, enterprise applications, Microsoft 365, SharePoint, Graph API, Power Platform, workflow tools, and internal supply chain systems where appropriate.
Establish CI/CD, automated testing, release management, telemetry, monitoring, incident response, and rollback practices for AI solutions deployed in production.
Define evaluation methods for LLM outputs, retrieval quality, prompt performance, model behavior, data quality, user feedback, and operational reliability.
Monitor production AI solutions for performance, cost, usage, failure modes, access issues, security risks, and continuous improvement opportunities.
Partner with AI Delivery to assess technical feasibility, estimate engineering effort, sequence development work, and shape solution scope for prioritized use cases.
Coordinate with IT, Cybersecurity, Data Governance, Analytics, and platform teams to resolve architecture, data access, integration, infrastructure, and compliance dependencies.
Provide technical guidance on what should be custom-built, reused, automated, or handled through existing enterprise platforms.