Engineer, AI Process Intelligence

micron; Hyderabad; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Micron Technology Hyderabad is seeking a Solutions Engineer to drive AI-driven process intelligence across Quality Systems. You will design, build, and deploy AI agents and automation workflows that address real operational pain points, enabling measurable improvements in efficiency and accuracy.

You will collaborate with Process Architects and stakeholders to ensure solutions are governance-compliant, scalable, and production-ready, leveraging LangChain, UiPath, and Power Automate in a

Qualifications

• Experience in building AI-enabled automation and production-ready AI agents.
• Familiarity with enterprise system integration and governance frameworks.
• Ability to design and deploy AI/automation solutions across Quality Systems.

Responsibilities

• Design, develop, and deploy AI agents addressing operational pain points in Quality Systems.
• Build AI agent networks aligned to AI infrastructure maturity model.
• Design and implement RPA workflows to automate high-volume tasks.

Skills

Python

LangChain

LangGraph

OpenAI APIs

UiPath

Power Automate

Data pipelines

APIs

Model deployment

Tools

UiPath

Power Automate

LangChain

LangGraph

Job description

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

JOB DESCRIPTION

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.

JOB RESPONSIBILITIES

AI Agent Development & Deployment [Required]

• 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

Automation Workflow Design & Implementation [Required]

• 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

Enterprise System Integration [Required]

• 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

Collaboration with Process Architects & Stakeholders [Required]

• 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

Testing, Validation & Performance Monitoring [Required]

• 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

Documentation & Knowledge Management [Required]

• 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

AI Solution Architecture & Technical Innovation [Preferred]

• 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

QUALIFICATIONS

Technical Knowledge Required:

• 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 syste