Assess current enterprise architecture and infrastructure readiness for Agentic AI
Perform fit-gap analysis between use case requirements and existing capabilities
Recommend architecture evolution strategies for AI enablement
Define scalable and modular Agentic AI reference architectures
Design and evaluate systems involving: Multi-agent orchestration and coordination, Tool use and API integrations, Memory management (short-term, long-term, vector stores), Reasoning and planning workflows
Ensure alignment with GenAI architecture patterns (RAG, prompt orchestration, fine-tuning strategies)
Establish evaluation pipelines for model and agent performance
Define structured validation frameworks (accuracy, hallucination, reliability, safety)
Implement end-to-end observability, including: Prompt and response tracing, Agent decision tracking, Performance metrics and alerting, Failure analysis and debugging workflows
Design deployment strategies for enterprise-grade AI systems in Azure
Ensure scalability, resiliency, and performance optimization
Integrate with CI/CD pipelines and DevOps workflows
Address security, compliance, and data governance requirements
Partner with system architects, AI engineers, platform teams, and business stakeholders
Translate complex AI concepts into clear architectural and business guidance
Drive alignment across teams and technology domains.

7-10 years of architecture experience required
Experience leading technical teams preferred
High School Diploma or equivalent required
Bachelor’s Degree in related field or equivalent work or military experience preferred.

Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.

Lead System Architect

Key skills