Senior AI Engineer

Join Micron's AI Enablement team and help accelerate enterprise-wide AI adoption. This role is designed for engineers passionate about applying AI to real-world business challenges. You will work on rapid prototyping, automation, and integration of AI solutions that enhance productivity and innovation across diverse business areas.

Key Responsibilities:

• AI Solution Development: Build and deploy AI-driven tools and workflows using platforms like Copilot Studio, UiPath, and other automation frameworks.
• Integration & Enablement: Connect AI agents with enterprise systems (e.g., SharePoint, M365), external APIs, knowledge bases, and ensure seamless interoperability.
• Process Automation: Identify repetitive tasks and design intelligent automation solutions to improve efficiency.
• Collaboration & Training: Partner with cross-functional teams to enable AI literacy, create best-practice documentation, and support internal training sessions.
• Governance & Compliance: Collaborate with cybersecurity teams to enforce data protection, threat modeling and ensure all AI solutions adhere to security, ethical, and compliance standards.

Security & Identity Integration:

• Ensure secure agent interactions using encryption, authentication, and authorization mechanisms.
• Integrate agents with identity platforms (e.g., OAuth2, OIDC, SAML, Entra ID, AD FS, etc.) for secure access control.

Continuous Improvement:

• Collect feedback, iterate solutions, and contribute to a culture of innovation and scalability.

Required Skills & Qualifications:

• Bachelor's or master's degree in computer science, AI, Machine Learning, Data Science or related field.
• Professionals with a minimum of 5 years of experience in software development, including at least 2 years specializing in AI/ML engineering.
• Strong understanding of AI concepts, machine learning pipelines, and automation tools.
• Hands-on experience or coursework in Copilot Studio, UiPath, and SharePoint.
• Knowledge with cloud AI platforms: Azure AI Foundry, AWS Bedrock, and/or Google Vertex AI.
• Knowledge with scalable context management solutions including retrieval-augmented generation (RAG), semantic chunking, and memory persistence for long-horizon tasks.
• Implement multi-agent workflows for complex tasks such as decision-making, negotiation, and collaborative problem-solving.
• Ability to design, implement, and manage context-aware systems that leverage Model Context Protocol (MCP) to maintain continuity across user interactions, including prompt engineering, memory management, and context window optimization for large language models.
• Familiarity with cloud platforms, API integrations, and data quality validation.
• Familiarity with agent orchestration frameworks and multi-agent systems using A2A (Agent to Agent).
• Knowledge of common development languages: .Net, C#, Python, Java, API development, SQL, PowerShell, Unix shell scripting.
• Excellent problem-solving skills and ability to work in fast-paced, agile environments.
• Strong communication skills for cross-team collaboration.

Preferred Attributes:

• Exposure to generative AI, prompt engineering, or agent-based systems.
• Interest in AI governance, security, and ethical frameworks.
• Ability to adapt quickly and deliver "quick wins" while maintaining enterprise standards.