New opportunity

Staff Solutions Engineer, EHSS Solutions

Micron Technology · Singapore

About this role

The Staff Solutions Engineer for EHSS (Environment, Health, Safety, and Sustainability) Solutions will design, develop, and validate digital capabilities to improve EHSS operations. This role focuses on leveraging AI enablement, workflow automation, analytics, and decision-support tools to transform business needs into scalable technical solutions. Responsibilities include leading technical design, prototyping, and pilot activities, ensuring alignment with enterprise architecture, security, and governance standards, and partnering with cross-functional teams including SMAI, IT, and EHSS SMEs to transition validated solutions into production. Required qualifications include a Bachelor's degree in a technical field and 5 or more years of experience in solution engineering, software development, analytics, or AI-enabled solutions. Candidates must demonstrate experience translating business requirements into scalable technical solutions, hands-on experience with application development and testing, and strong communication skills. Preferred qualifications include experience with enterprise AI platforms such as Microsoft Copilot Studio, Azure AI Services, and Azure OpenAI, as well as proficiency in Python, C#, .NET, and various enterprise data platforms like Snowflake and GCP. Experience supporting regulated business functions such as EHSS, Quality, or Supply Chain is highly valued.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

AI-enabled solutionsWorkflow automationAnalyticsDecision-support toolsSQLPythonC#.NETMicrosoft Copilot StudioPower PlatformAzure AI ServicesAzure OpenAISnowflakeGoogle Cloud PlatformAzure Data ServicesSQL ServerPower BITableauSAP S/4HANASAP ECCServiceNowAPI developmentSystem integration

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Scalable Digital Solution Design
The role requires translating complex EHSS business requirements into scalable, reusable technical patterns. You must demonstrate the ability to move beyond one-off scripts to build robust, maintainable applications that align with enterprise architecture, security, and governance standards.
AI and Automation Integration
A primary focus is leveraging AI enablement and workflow automation to improve EHSS operations. You must be prepared to design and validate solutions using enterprise platforms like Microsoft Copilot Studio, Azure AI, and Power Platform to enhance decision-support capabilities.
Cross-Functional Stakeholder Collaboration
Success depends on partnering with EHSS SMEs, IT, and SMAI teams. You must be able to communicate technical risks, trade-offs, and design decisions clearly to non-technical collaborators to ensure smooth transitions from prototyping to production.

Likely challenges to think through

Navigating Regulated Environment Constraints
EHSS is a highly regulated function. The challenge lies in balancing the speed of AI innovation with strict requirements for data validation, human oversight, and security. Prepare by discussing how you have implemented 'human-in-the-loop' controls or validated AI outputs in previous regulated or mission-critical projects.
Transitioning Prototypes to Production
The role emphasizes leading pilot activities and transitioning them into production. A common difficulty is 'pilot purgatory,' where solutions fail to scale due to integration issues or lack of sustainment planning. Prepare by highlighting your experience in designing for long-term supportability and system interoperability.

Practice your answers

Technical practice

Designing Scalable AI-Enabled Solutions

What to coverExplain your approach to translating complex business requirements into scalable technical architectures. Focus on how you ensure solutions remain modular, reusable, and aligned with enterprise governance and security standards.

Integrating Enterprise AI Platforms

What to coverDescribe your experience with platforms like Azure AI Services or Microsoft Copilot Studio. Discuss how you manage the trade-offs between using pre-built AI services versus developing custom models for specific EHSS or operational needs.

Data Pipeline and Analytics Strategy

What to coverHow do you ensure data integrity and security when building analytics products using platforms like Snowflake or GCP? Address the importance of using trusted data assets and implementing proper monitoring and human oversight in decision-support tools.

Workflow Automation in Regulated Environments

What to coverDiscuss your experience automating workflows within regulated functions like EHSS or Supply Chain. Explain how you balance the need for operational efficiency with the strict compliance and validation requirements inherent in these sectors.

API Development and System Integration

What to coverDetail your process for building and consuming APIs to integrate disparate enterprise systems like SAP S/4HANA or ServiceNow. Focus on how you handle interoperability challenges and ensure robust communication between services.

Prototyping and Pilot Execution

What to coverExplain your methodology for moving from a minimum viable solution (MVS) to a production-ready application. Suggestion: Highlight how you use feedback from pilot activities to refine technical design and improve scalability.

Technical Problem-Solving and Systems Thinking

What to coverProvide an example of how you identified a technical bottleneck in a complex system. Describe how you evaluated the feasibility of potential solutions and the impact of your chosen approach on long-term system sustainment.

Application Development with .NET and Python

What to coverCompare the use of Python and C#/.NET in the context of enterprise solution engineering. Explain how you choose the appropriate technology stack based on performance requirements, existing infrastructure, and team expertise.

Behavioural practice

Cross-Functional Collaboration

What to coverDescribe a situation where you had to align business, IT, and AI teams on a technical project. How did you manage competing priorities and ensure all stakeholders were satisfied with the final solution?

Communicating Technical Risks to Non-Technical Stakeholders

What to coverGive an example of when you had to explain a complex technical risk or trade-off to a non-technical partner. How did you adjust your communication style to ensure they understood the implications for the business?

Managing Global or Multi-Site Initiatives

What to coverShare an experience where you supported a technology initiative across multiple global sites. How did you handle regional differences in requirements, data availability, or operational processes?

Driving Technical Innovation

What to coverDescribe a time you identified an opportunity to improve an existing process using AI or automation. What steps did you take to advocate for the initiative and lead the design and validation process?

Sharpen your knowledge

Topics to prepare

Enterprise AI Governance and Security
The role requires ensuring AI solutions align with security, governance, and human oversight standards. Exercise: Review the NIST AI Risk Management Framework and map its core functions to a hypothetical EHSS data-processing workflow to demonstrate how you would mitigate risks like bias or unauthorized data access.
Systems Thinking for Regulated Environments
You must translate business requirements into scalable solutions for EHSS, which is a highly regulated function. Exercise: Create a high-level architectural diagram showing how an automated EHSS reporting tool integrates with existing enterprise systems like SAP or ServiceNow while maintaining data integrity and compliance.

Skills to revise

Enterprise AI Platform Integration
The role prioritizes experience with Microsoft Copilot Studio and Azure AI Services. Exercise: Design a prototype workflow in Microsoft Power Platform that uses an Azure OpenAI connector to summarize EHSS incident reports, focusing on how you would handle data validation and user feedback loops.
API Development and System Integration
Building and consuming APIs is essential for connecting disparate enterprise data platforms. Exercise: Draft a technical plan for integrating a new analytics dashboard with an existing SQL Server or Snowflake data warehouse, specifically detailing your approach to authentication, error handling, and data synchronization.
Python for Data-Driven Solutions
Python is a preferred language for developing analytics and AI-enabled capabilities. Exercise: Write a script that performs a basic data transformation or cleaning task on a sample EHSS dataset, demonstrating your ability to prepare data for downstream analytics or decision-support tools.

Your preparation checklist

Prepare a portfolio of AI-enabled solution case studies
Document 2-3 projects where you translated business requirements into technical solutions using AI, automation, or analytics. Focus on the 'why' behind your design choices, how you validated the prototype, and the measurable impact on operational efficiency or risk management.
Map your technical stack to enterprise requirements
Create a summary table matching your experience in Python, C#, .NET, and cloud platforms (Azure/GCP) to the specific needs of EHSS or similar regulated environments. Highlight your ability to integrate these with enterprise systems like SAP or ServiceNow.
Develop a framework for technical communication
Prepare to explain complex technical trade-offs—such as choosing between a custom-built model and an off-the-shelf Azure AI service—to non-technical stakeholders in EHSS, ensuring they understand the risks, governance, and scalability implications.
Formulate questions on EHSS data governance
Prepare thoughtful questions regarding how Micron manages 'trusted data' for EHSS, the current maturity of their AI-enabled workflows, and how the team balances rapid prototyping with enterprise security and compliance standards.
Review your experience with regulated business functions
Reflect on your past work in highly regulated sectors like Supply Chain, Quality, or Manufacturing. Be ready to discuss how you handled data integrity, human oversight, and regulatory compliance when deploying automated or AI-driven decision-support tools.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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