Senior AI Engineer

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 Summary:

We are   seeking   a technically proficient and proactive   Senior AI Engineer   to support, develop, and enhance cloud-based AI solutions, AI Agents, and custom applications across   Microsoft Azure, Amazon Web Services AWS, and Google Cloud Platform GCP . This role will   be responsible for   designing, developing, deploying, and supporting enterprise-grade AI applications, agentic solutions, RAG-based systems, automation workflows, and cloud-native integrations.

The ideal candidate should have strong hands-on experience in   AI Agent development, application development, multi-cloud AI platforms, backend and frontend engineering, DevOps, CI/CD, Infrastructure as Code, security, monitoring, and operational excellence . The role requires deep technical   expertise , strong troubleshooting skills, and the ability to collaborate with cloud, application, data, security, and platform teams to deliver scalable, secure, and reliable AI capabilities.

Key Responsibilities:

1. AI Agent Development and Engineering

- Design, develop, and deploy AI Agents using cloud-native and open-source agent frameworks.

- Build agentic workflows using   Azure AI Foundry Agent Service ,   AWS Bedrock   AgentCore ,   LangGraph ,   Strands Agents SDK ,   Semantic Kernel , and   AutoGen .

- Implement   tool /function calling, memory, state management, checkpointing, multi-agent orchestration, and agent-to-agent workflows.

- Integrate enterprise tools, APIs, databases, knowledge bases, and automation systems using   MCP Model Context Protocol   and custom connectors.

- Design and implement   RAG Retrieval-Augmented Generation   solutions using vector stores, knowledge bases, and search services.

- Develop guardrails, prompt evaluation, content safety controls, tracing, and observability for AI Agent solutions.

- Optimize   AI Agent performance, cost, latency, reliability, and user experience.

2. Custom Application Development

- Develop scalable web applications and internal tools to enable AI, automation, and cloud service capabilities.

- Build frontend applications using   React ,   TypeScript , REST API integration,   GraphQL   integration, and secure authentication flows.

- Implement authentication and authorization using   OAuth2 ,   OIDC , and   MSAL .

- Develop backend services using   C#/.NET ,   Python   FastAPI , or   Node.js .

- Design and build microservices, APIs, event-driven services, and cloud-native integrations.

- Work with relational and NoSQL databases including   SQL ,   Cosmos DB , and   DynamoDB .

- Integrate messaging and event-driven platforms such as   Azure Service Bus ,   AWS SQS , and   AWS SNS .

- Implement backend testing, API testing, unit testing, integration testing, and code quality practices.

- Ensure application solutions are secure, scalable, maintainable, and aligned with enterprise architecture standards.

3. Cloud AI Services Support

- Deploy, manage, and support AI/ML workloads across Azure, AWS, and GCP.

- Support   Azure AI Foundry ,   Azure OpenAI ,   Azure AI Search , model deployments, evaluation, tracing, tool/function calling, and content safety controls.

- Support   AWS Bedrock ,   Bedrock Studio ,   Amazon Q Business ,   Bedrock Knowledge Bases ,   Guardrails , and   Bedrock   AgentCore .

- Support   GCP Vertex AI ,   Vertex AI Search , and   Gemini Models .

- Ensure secure and compliant deployment of AI services, APIs, agents, and applications.

4. Cloud Operations and Optimization

- Resolve complex cloud infrastructure and AI platform issues across Azure, AWS, and GCP.

- Perform root cause analysis for incidents related to AI services, agents, applications, APIs, integrations, and cloud platforms.

- Manage and   optimize   cloud resources including   compute , storage, networking, databases, containers, and AI services.

- Implement and   monitor   backup, disaster recovery, high availability, resiliency, and operational readiness.

- Identify   automation opportunities to reduce manual effort and improve operational efficiency.

- Optimize   cloud and AI workloads for cost, performance, security, and reliability.

5. Automation,   DevOps   and CI/CD

- Develop automation using   PowerShell ,   Python ,   Terraform , and cloud-native tools.

- Implement Infrastructure as Code using   Terraform   and   Bicep .

- Design and maintain CI/CD pipelines using   GitHub Actions   and   Azure DevOps .

- Automate build, test, security scan, deployment, and environment promotion workflows.

- Support containerized deployments and cloud-native release patterns.

- Integrate automated validation, testing, approval gates, and release controls.

- Improve deployment reliability for AI Agents, APIs, applications, infrastructure, and cloud services.

6. Version Control and Engineering Practices

- Use   Git   effectively for source control, branching, merging, pull requests, and code reviews.

- Follow branching strategies such as   trunk-based development   or   GitFlow .

- Manage code repositories in   GitHub ,   Azure Repos , or   GitLab .

- Resolve merge conflicts and   maintain   clean,   reviewable   code   history.

- Participate in PR reviews, enforce coding standards, and promote secure development practices.

- Maintain reusable templates, libraries, automation scripts, and shared engineering assets.

7 . Observability, Reliability and Support

- Implement monitoring, logging, tracing, and   alerting for   AI Agents, applications, APIs, and cloud services.

- Support observability for AI platforms including agent traces, tool calls, model interactions, latency, failure rates, and usage trends.

- Troubleshoot production issues involving AI workflows, integrations, authentication, service connectivity, and cloud resources.

- Participate in rotational support or   on-call   activities as   required .

- Contribute to operational readiness reviews, incident management, and continuous improvement.

Required Skills and Qualifications

Education

- Bachelor’s degree in Computer Science , Information Technology, Engineering, or   a related   field.

Core Technical Skills

- Hands-on experience with cloud-native AI services, model deployment, RAG implementation, and AI platform operations.

- Strong programming and scripting skills in   Python ,   PowerShell , and at least one backend language such as   C#/.NET ,   Node.js , or   Python   FastAPI .

- Experience building APIs, microservices, automation workflows, and production-grade integrations.

- Experience with SQL and NoSQL databases including   Cosmos DB ,   DynamoDB , and relational databases.

- Experience with vector stores, search platforms, knowledge bases, and enterprise data integration.

- Strong understanding of DevOps, CI/CD,   IaC , containerized deployments, and release automation.

- Solid understanding of cloud security, networking, identity, compliance, monitoring, and operational support.

AI and Agent Development Skills

- Hands-on experience with   Azure AI Foundry Agent Service , model deployment, tool/function calling, RAG over Azure AI Search, evaluations, tracing, and content safety.

- Hands-on experience or strong working knowledge of   AWS Bedrock   AgentCore , including Runtime, Gateway, Memory, Identity, observability, Bedrock models, Knowledge Bases, and Guardrails.

- Experience with agent frameworks such as   LangGraph ,   Strands Agents SDK ,   Semantic Kernel , and   AutoGen .

- Understanding of   MCP Model Context Protocol   for tool and system integration.

- Strong knowledge of agent fundamentals including RAG, tool use, prompt engineering, prompt evaluation, memory/state design, multi-agent patterns, cost optimization, and guardrails.

Application Development Skills

- Frontend development experience with   React   and   TypeScript .

- Experience integrating frontend applications with REST and   GraphQL   APIs.

- Experience implementing secure auth flows using   OAuth2 ,   OIDC , and   MSAL .

- Backend development experience with   C#/.NET ,   Python   FastAPI , or   Node.js .

- Experience designing APIs, building microservices, and implementing robust testing practices.

- Experience with messaging services such as   Azure Service Bus ,   AWS SQS , and   AWS SNS .

DevOps, Version Control and CI/CD Skills

- Strong Git   proficiency   including branching strategies, pull request workflows, code reviews, and merge-conflict resolution.

- Experience with   GitHub ,   Azure Repos , or   GitLab .

- Experience designing CI/CD pipelines using   GitHub Actions   or   Azure DevOps .

- Experience with automated build, test, deploy, and release promotion across environments.

- Experience with   IaC -driven releases using   Terraform   and/or   Bicep .

- Experience supporting containerized application deployments.

Preferred Certifications

- Microsoft Certified: Azure AI Engineer Associate.

- Microsoft Certified: Azure Solutions Architect Associate or Expert.

- AWS Certified Solutions Architect Associate or Professional.

- AWS Certified Machine Learning Specialty or AWS AI/ML-related certification.

- Google Professional Cloud Architect.

- Google Professional Machine Learning Engineer.

- Terraform, Kubernetes, DevOps, or security-related certifications are a plus.

Soft Skills

- Strong analytical and problem-solving skills.

- Ability to troubleshoot complex cloud, AI, application, and integration issues.

- Strong communication   and collaboration skills .

- Ability to work with cross-functional teams across cloud, application, data, security, and operations.

- Ability to mentor junior engineers and contribute to team growth.

- Proactive mindset with   focus   on automation, reliability, cost optimization, and continuous improvement.

- Ability to document clearly and communicate technical concepts to both technical and non-technical stakeholders.

Work Environment

- May require rotational shifts or   on-call   support.

- On-site work: 5 days.

About Micron Technology, Inc.

We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life   for all . With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience.

To learn more, please visit micron.com/careers

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

To request assistance with the application process and/or for reasonable accommodations,   please contact [email protected]

Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.

Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.

AI alert : Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.

Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.