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 hrsupport_india@micron.com
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.
