Senior AI Engineer, Multi-Agent Systems

Our client is looking TECHNOLOGY ARCHITECT/Senior AI Engineer (Applied AI) for Contract project in Blaine, MN (Hybrid) below is the detailed requirements.

Job Title : TECHNOLOGY ARCHITECT/Senior AI Engineer (Applied AI)
Location : Blaine, MN (Hybrid)
Duration :  Long term  

Job Description:

• Bachelor’s degree in related field
• Design end-to-end Agentic AI architectures integrating AI agent lifecycle frameworks, data infrastructure, orchestration, and enterprise platforms.
• Develop and refine AI agent lifecycle strategies covering agent creation, validation, deployment, monitoring, versioning, and retirement.
• Architect modular and reusable AI agent frameworks supporting orchestration, interoperability, reusable components, and rapid ecosystem development.
• Define AI agent data infrastructure covering data ingestion, processing, storage, access patterns, data quality, scalability, security, and resilience.
• Establish Agentic AI governance frameworks with policies, guardrails, accountability mechanisms, risk controls, ethics, compliance, and transparency.
• Collaborate with Product, Engineering, Security, Risk, and Operations teams to implement AI agent engineering best practices.
• Establish standards for testing, observability, monitoring, version control, incident management, and reliability of AI agents.
• Design secure hybrid-work collaboration patterns, access controls, and workflow automations that enable distributed teams to effectively interact with AI agents.
• Provide technical guidance for enterprise AI agent integrations, focusing on performance optimization, fault tolerance, scalability, and maintainability.
• Review existing AI agent implementations, identify architectural gaps and optimization opportunities, and recommend actionable improvements.
• Create architecture documentation, reference architectures, design standards, and reusable patterns for enterprise Agentic AI implementations.
• Partner with Risk, Security, and Compliance stakeholders to identify and mitigate risks related to agent behavior, data usage, privacy, and automated decision-making.
• Mentor technical teams on AI agent engineering, frameworks, architecture patterns, data infrastructure, and governance best practices.
• Evaluate emerging Agentic AI technologies, frameworks, tools, and methodologies and translate relevant innovations into practical enterprise architecture recommendations.
• Ability to communicate technical AI concepts effectively to business and leadership stakeholders