Overview

JR106415 Engineer, AI Process Intelligence

Responsibilities

• The Solutions Engineer sits within the Transform the Business pillar of Quality Systems and serves as the technical execution engine of the AI Process Intelligence team. This role operates at the intersection of process intelligence, automation engineering, and enterprise system integration—building production-ready AI agents, predictive models, and intelligent workflows that solve real operational pain points across Micron's Quality Management System.
• The Solutions Engineer works hand-in-hand with Process Architects (who design and optimize the business processes) to ensure that solutions are architecturally sound, automation-ready, and aligned with Micron's AI governance framework.
• Design, develop, and deploy purpose-built AI agents that address real operational pain points across Quality Systems
• Build and maintain AI agent networks aligned to the QMS AI infrastructure maturity model
• Develop agentic workflows using frameworks such as LangChain, LangGraph, and Microsoft Copilot Studio, etc., ensuring agents are testable, governable, and production-ready
• Conduct User Acceptance Testing (UAT) with process stakeholders, collect structured feedback, and iterate to meet performance and accuracy thresholds
• Deploy AI solutions to production environments and establish monitoring, feedback loops, and lifecycle management practices
• Design and implement Robotic Process Automation (RPA) workflows using tools such as UiPath or Power Automate to eliminate high-volume, repetitive manual tasks
• Build and integrate predictive models and intelligent workflows that improve cycle times, reduce operational errors, and increase team capacity
• Execute automation initiatives to meet labor productivity, optimization, and efficiency gain targets
• Integrate AI and automation solutions with Micron's enterprise platforms.
• Support the Data Ecosystem development by ingesting controlled documents, process models, and requirements data into a unified AI-enabled platform
• Ensure all solutions comply with Micron's AI governance framework, data privacy protocols, and information security requirements
• Partner with Process Architects to understand process designs, business rules, and workflow requirements ensuring alignment between process intent and technical implementation
• Engage cross-functional stakeholders to gather requirements, validate solutions, and drive adoption
• Participates in Council meetings and project forums to communicate solution status, risks, dependencies, and value delivered
• Support change management activities including stakeholder communications, training, and go-live support for AI deployments
• Conduct structured testing and validation of AI agents and automation tools, including functional testing, accuracy benchmarking, and edge case analysis
• Define and track key performance indicators (KPIs) for deployed solutions (e.g., cycle time reduction, labor productivity savings, accuracy rates, adoption metrics)
• Monitor production performance and implement iterative improvements based on data insights and stakeholder feedback
• Troubleshoot and resolve technical issues with deployed AI agents and automation workflows in a timely manner
• Maintain clear and up-to-date technical documentation for all developed solutions, including architecture diagrams, integration maps, testing records, and deployment guides
• Contribute to the Data Eco System by ensuring solution artifacts, learnings, and best practices are captured and accessible
• Support the team's AI project portfolio management, including project charters, proof-of-concept documentation, and project closure reports
• Apply knowledge of data engineering and model deployment practices to build scalable, maintainable AI solutions
• Explore and prototype emerging AI technologies (e.g., multi-agent orchestration, agentic AI architectures) to advance Micron's AI process intelligence capabilities
• Mentor junior team members and contribute to the team's AI literacy and capability building
• Design and implement end-to-end automation workflows that reduce manual effort
• Work in iterative cycles with structured sprint planning and delivery
• Manage solution development lifecycle using Agile/project management principles

Qualifications

• Machine learning and AI frameworks (e.g., Python, LangChain, LangGraph, OpenAI APIs)
• Robotic Process Automation (RPA) platforms (e.g., UiPath, Power Automate)
• Data engineering and model deployment practices (data pipelines, APIs, model lifecycle)
• Enterprise system integration (Salesforce, Teamcenter, SAP, ServiceNow, Microsoft 365)
• AI agent architecture and agentic AI systems (multi-agent design, orchestration, feedback loops)
• AI validation, testing, and performance monitoring methodologies
• Understanding of Micron's process and system architecture (QMS, MMS, BPM framework)
• Familiarity with ISO 9001 / IATF 16949 quality management standards (Preferred)
• Building and deploying AI agents or chatbot solutions in enterprise environments
• Integrating AI/ML models
• Working in a Quality Management, Manufacturing, or Operations domain
• Delivering measurable labor productivity improvements through automation
• Exposure to ISO 9001 / IATF 16949 quality standards or QMS environments

Education

• Microsoft Azure AI Fundamentals / AI Engineer Associate
• UiPath RPA Developer / Advanced RPA Developer
• Python for Data Science / Machine Learning (Coursera, edX)
• LangChain / LangGraph Developer Certification
• Microsoft Copilot Studio Certification
• Hiring managers may view your performance appraisals, original resume, transcripts or other performance-related documentation in your personal file. This information will be held in confidence.
• If you are selected to interview for a position, you must notify your direct supervisor before participating in the interview process.
• Minimum Education
• Bachelor's Degree in Computer Science, Data Science, Software Engineering, Electrical Engineering, Information Technology, or a related technical field
• Master's Degree in Computer Science, AI/Machine Learning, Data Engineering, or equivalent advanced technical discipline