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. Automatio…