New opportunity

Staff Solutions Engineer, EHSS Solutions

Micron Technology · Hyderabad, India

About this role

As the Solutions Engineer, EHSS Solutions, you will design, develop, and validate digital capabilities that improve EHSS operations through analytics, automation, AI-enabled solutions, intelligent workflows, and decision-support tools. You will partner with EHSS SMEs, site teams, PMO, SMAI, IT, and technology partners to transform business needs into scalable and supportable digital solutions.

Responsibilities

Design, develop, and validate AI-enabled solutions, intelligent workflows, analytics capabilities, automation tools, and internal EHSS applications.
Translate business requirements and operational processes into scalable technical solutions, prototypes, and reusable solution patterns.
Build and integrate solutions using enterprise platforms, APIs, trusted data assets, and approved technology services.
Ensure solutions align with enterprise architecture, security, governance, interoperability, and sustainment requirements.
Identify and evaluate opportunities where AI, analytics, automation, or digital technologies can improve EHSS outcomes.
Lead technical design, prototyping, testing, validation, and pilot execution for approved initiatives.
Assess technical feasibility, scalability, risks, dependencies, and implementation approaches for proposed solutions.
Partner with EHSS, PMO, SMAI, IT, and technology providers to shape solution approaches and transition validated solutions into production deployment.
Develop analytics, decision-support, and AI-enabled capabilities that improve operational visibility, risk management, and decision-making.
Ensure solutions leverage trusted enterprise data and appropriate controls, validation, monitoring, security, and human oversight.
Contribute reusable technical practices, solution standards, and innovation capabilities that support long-term scalability across EHSS.

Required qualifications

Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, Engineering, or a related discipline.
7 or more years of experience in solution engineering, software development, analytics, automation, AI-enabled solutions, or related technical disciplines.
Demonstrated experience translating business and process requirements into scalable technical solutions.
Hands-on experience designing, building, testing, and validating applications, automation solutions, analytics products, or AI-enabled capabilities.
Experience developing prototypes, pilots, or minimum viable solutions and using results to improve solution design.
Experience working with APIs, integrations, cloud platforms, or enterprise application technologies.
Working knowledge of SQL, enterprise data platforms, cloud technologies, and analytics-ready data concepts.
Strong technical problem-solving, systems-thinking, and solution-design skills.
Ability to collaborate effectively across business, data, systems, IT, and AI teams.
Strong communication skills and the ability to explain technical concepts, risks, and trade-offs to non-technical stakeholders.

Preferred qualifications

Experience developing AI-enabled solutions, workflow automation, analytics products, or decision-support capabilities.
Experience with Microsoft Copilot Studio, Power Platform, Azure AI Services, Azure OpenAI, or comparable enterprise AI and automation platforms.
Experience with Python, C#, .NET, or comparable application-development technologies.
Experience working with Snowflake, Google Cloud Platform (GCP), Azure Data Services, SQL Server, Power BI, Tableau, or comparable enterprise data and analytics platforms.
Experience building and consuming APIs, enterprise services, and system integrations.
Experience with SAP S/4HANA, SAP ECC, ServiceNow, or other enterprise business systems.
Experience supporting EHSS, Quality, Manufacturing, Facilities, Supply Chain, or other regulated business functions.
Experience supporting global or multi-site technology initiatives.
Relevant certifications in AI, cloud platforms, software development, data analytics, automation technologies, or related disciplines.

Benefits

Choice of medical, dental, and vision plans in all locations
Benefit programs that help protect income if unable to work due to illness or injury, and paid family leave
Robust paid time-off program and paid holidays

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 automationAnalyticsMicrosoft Copilot StudioPower PlatformAzure AI ServicesAzure OpenAIPythonC#.NETSnowflakeGoogle Cloud Platform (GCP)Azure Data ServicesSQL ServerPower BITableauAPIsSAP S/4HANASAP ECCServiceNowSQL

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

Designing and Prototyping AI-Enabled EHSS Solutions
A core mandate is leading technical design, prototyping, and pilot execution for intelligent workflows, analytics capabilities, and internal EHSS applications using platforms like Microsoft Copilot Studio, Azure OpenAI, and Power Platform.
Translating Business Requirements into Scalable Architectures
Bridging the gap between operational processes and enterprise technology by converting EHSS business needs into robust, secure, and supportable solution patterns that adhere to governance and architecture standards.
Cross-Functional Collaboration and Stakeholder Engagement
Partnering effectively with EHSS SMEs, site teams, PMO, SMAI, and IT delivery teams to shape solution approaches, transition pilots into production, and explain technical risks and trade-offs to non-technical stakeholders.
Ensuring Data Integrity, Security, and Human Oversight
Guaranteeing that analytics and decision-support tools leverage trusted enterprise data while embedding appropriate validation, monitoring, security controls, and human oversight into AI deployments.

Likely challenges to think through

Balancing Rapid AI Prototyping with Strict Enterprise Governance
The challenge lies in quickly building MVPs and leveraging enterprise AI tools while ensuring strict compliance with corporate security, architecture, and governance standards. Prepare by reviewing standard enterprise integration frameworks and practicing how to document security and compliance trade-offs for technical governance boards.
Translating Complex Regulatory EHSS Domain Needs into Technical Specifications
Environment, Health, Safety, and Sustainability (EHSS) processes involve specialized, regulated workflows that may be unfamiliar to software engineers. Prepare by studying standard manufacturing safety metrics, compliance reporting structures, and methods for conducting rigorous discovery sessions with domain subject matter experts.
Managing Multi-Site and Cross-Functional Alignment
Driving technology initiatives across global or multi-site teams requires aligning diverse stakeholders from IT, data, and operational units. Prepare by developing structured communication frameworks to manage expectations, dependencies, and rollout timelines across disparate operational groups.

Practice your answers

Technical practice

Designing AI-Enabled Workflows for Regulated Functions

What to coverDiscuss how you would approach designing an AI-enabled workflow or decision-support tool for EHSS (Environment, Health, Safety, and Sustainability) operations. Address how you balance automation efficiency with appropriate validation, security controls, and human oversight as mandated by enterprise standards.

Prototyping with Enterprise AI Platforms

What to coverExplain your experience and strategy for building minimum viable products (MVPs) using enterprise AI and automation platforms like Microsoft Copilot Studio, Power Platform, or Azure OpenAI services. Focus on how pilot results are captured and used to refine final solution designs.

Integrating Enterprise APIs and Cloud Services

What to coverDescribe the architectural patterns and security considerations involved in building and consuming APIs to integrate cloud platforms like Azure Data Services or Snowflake with existing enterprise systems. Emphasize compliance with enterprise governance and interoperability requirements.

Data Modeling and SQL for Analytics-Ready Platforms

What to coverExplain how you optimize SQL queries and structure analytics-ready data concepts to support operational visibility and risk management dashboards. Cover how you ensure data assets remain trusted and secure across multi-site initiatives.

Application Development in Python and .NET

What to coverCompare the strengths of Python versus C#/.NET when developing internal applications, automation tools, or custom backend services. Discuss considerations for scalability, maintainability, and integration with enterprise business systems like SAP or ServiceNow.

Translating Business Requirements into Scalable Solution Patterns

What to coverWalk through your methodology for gathering operational requirements from domain subject matter experts and converting them into reusable solution patterns. Highlight how you assess technical feasibility, risks, and implementation dependencies.

Ensuring Security, Governance, and Compliance in Solutions

What to coverExplain the key architectural principles you implement to ensure digital solutions align with enterprise security, governance, and sustainment requirements. Discuss how you handle data privacy and monitoring in cloud environments.

Leveraging Enterprise Business Systems in Solutions

What to coverDiscuss how you integrate solutions with enterprise business systems such as SAP S/4HANA, SAP ECC, or ServiceNow to streamline workflows across manufacturing, supply chain, or quality functions. Focus on handling complex system dependencies.

Behavioural practice

Translating Complex Technical Concepts for Non-Technical Stakeholders

What to coverDescribe a situation where you had to explain technical risks, AI capabilities, or system trade-offs to non-technical business leaders or EHSS subject matter experts. Use the Situation-Action-Result format to explain how you ensured alignment and secured stakeholder buy-in.

Collaborating Across Cross-Functional Teams

What to coverProvide an example of a time you collaborated effectively across disparate business, data, systems, IT, and AI teams on a global or multi-site technology initiative. Detail your specific actions to manage competing priorities and drive the project to completion.

Managing Scope and Technical Feasibility in Prototyping

What to coverShare an instance where an initial AI or automation prototype faced unforeseen technical constraints or scalability risks during pilot execution. Explain how you assessed the trade-offs, adapted the approach, and partnered with delivery teams to transition a validated solution into production.

Driving Technical Innovation and Continuous Improvement

What to coverRecount a scenario where you identified an opportunity to apply digital technologies, analytics, or automation to improve operational outcomes in a regulated environment. Describe how you evaluated the opportunity, designed the solution pattern, and contributed reusable practices for long-term scalability.

Sharpen your knowledge

Topics to prepare

Enterprise AI Solutions & Workflow Automation
Review how to design, prototype, and validate AI-enabled workflows and decision-support capabilities using enterprise platforms like Microsoft Copilot Studio, Power Platform, and Azure OpenAI. Relevant because the role centers on building intelligent workflows and automation tools to improve EHSS operations.
Enterprise Architecture, Security, and Governance
Study frameworks for ensuring solutions align with enterprise security, governance, data controls, and human oversight requirements. Relevant because solutions must comply with corporate architecture standards and maintain trusted data assets.
Business Requirements Translation and Systems-Thinking
Practice converting operational processes and business needs from non-technical stakeholders into scalable solution patterns and prototypes. Relevant because the position requires partnering closely with EHSS SMEs to transform operational challenges into digital solutions.

Skills to revise

Cloud and Enterprise Application Integration
Revise building and consuming APIs, enterprise services, and system integrations across cloud platforms like Azure Data Services and Snowflake. Relevant because the role involves integrating solutions using enterprise platforms and approved cloud technology services.
Application Development with Python and C#/.NET
Practice coding and prototyping using Python, C#, or .NET for application development and automation tasks. Relevant because these are explicitly cited as preferred technologies for building custom solutions and internal applications.
Enterprise Data Platforms and SQL
Refresh SQL querying and analytics-ready data concepts for working with enterprise data platforms and relational databases like SQL Server. Relevant because the position requires working knowledge of SQL and enterprise data platforms to build analytics capabilities.
Enterprise Systems and Business Platforms
Familiarize yourself with enterprise business systems such as SAP S/4HANA, SAP ECC, or ServiceNow. Relevant because experience supporting regulated business functions and enterprise platforms is highlighted as a key preference for the role.

Your preparation checklist

Prepare an AI Workflow and Prototyping Walkthrough
Compile a structured case study or portfolio overview demonstrating how you designed, prototyped, and validated an AI-enabled solution, automated workflow, or decision-support tool using platforms like Azure OpenAI, Copilot Studio, or the Power Platform.
Document Enterprise Integration and API Experience
Draft concrete examples of how you have successfully built and consumed APIs, connected cloud platforms (such as Azure Data Services or Snowflake), and integrated systems while adhering to enterprise security, governance, and architecture standards.
Synthesize Requirements Translation and Stakeholder Communication Examples
Prepare STAR-format examples illustrating your ability to work with non-technical subject matter experts (such as EHSS or operations teams), translate business processes into scalable technical solutions, and explain technical risks and trade-offs.
Review Data Engineering and Analytics Competencies
Brush up your proficiency in SQL, enterprise data platforms, and analytics concepts (such as Power BI or Tableau) to demonstrate your capability to build trusted data assets that improve operational visibility and risk management.
Formulate Targeted Questions for the Interviewers
Develop thoughtful questions regarding Micron's Global EHS & Sustainability operating model, how solutions transition from pilot phases to production deployment across multi-site manufacturing facilities, and collaboration workflows with SMAI and IT teams.

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