Lead System Architect

Why GM Financial TechnologyInnovation isn’t just a talking point at GM Financial, it’s how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We’re committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry.Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact.What makes you an ideal candidate?Assess enterprise architecture, infrastructure, and cloud readiness for Agentic AIEvaluate use cases through fit-gap analysis, feasibility, scalability, and riskDefine and evolve scalable, modular architectures for Agentic AI and GenAI solutionsDesign systems across orchestration, tool integration, memory, and reasoning workflowsApply best practices for GenAI (RAG, prompt orchestration, fine-tuning)Establish validation frameworks and performance evaluation (accuracy, reliability, safety)Implement end-to-end observability (tracing, monitoring, metrics, debugging)Lead deployment of enterprise AI solutions in Azure with strong security and governanceIntegrate AI into cloud-native, microservices environments using modern DevOps practicesPartner across teams to translate business needs into technical solutions and drive alignmentPromote standards, best practices, and responsible AI adoptionMentor teams and communicate complex AI concepts clearly to diverse stakeholdersExperience7-10 years of architecture experience requiredExperience leading technical teams preferredHigh School Diploma or equivalent requiredBachelor’s Degree in related field or equivalent work or military experience preferredWhat We Offer: 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. Our Culture: Our team members define and shape our culture. We have an environment that welcomes new ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than. work — we thrive. Compensation: Competitive salary and bonus eligibility; this role is eligible for company vehicle program. Work Life Balance: Flexible hybrid work environment, 2-days a week in office. About the role: The Lead Systems Architect – Agentic AI holds a critical role at the intersection of enterprise architecture, emerging AI capabilities, and business value realization. This role serves both as a technical strategist and a hands-on architecture leader, with a strong emphasis on evaluating how Agentic AI and GenAI capabilities can be effectively and safely integrated into the existing enterprise ecosystem.As a technical leader, this role is responsible for assessing current architecture and infrastructure, conducting feasibility studies, and mapping business use cases and requirements to the organization’s AI and system capabilities. The Lead Systems Architect – Agentic AI ensures that proposed solutions are practical, scalable, observable, and production-ready, while aligning with enterprise standards and constraints.This role requires deep expertise in Agentic AI and Generative AI architectures, including orchestration patterns, tool usage, memory, reasoning workflows, and decision frameworks. The architect must also ensure robust validation mechanisms, observability frameworks, and production deployment strategies for AI systems.As a performance leader, this role partners with system architects, engineering teams, and business stakeholders to drive clarity, alignment, and execution, while mentoring teams on modern AI architecture practices, responsible AI principles, and production-grade deployments.In this role you will: Define and drive enterprise strategy for Agentic AI and GenAI aligned to business goalsAssess systems, cloud, and infrastructure readiness for AI adoptionEvaluate AI use cases for feasibility, scalability, cost, risk, and complianceTranslate business needs into architecture; identify gaps and recommend solutionsDesign reference architectures and patterns (orchestration, tools, memory, reasoning)Establish validation and observability approaches (testing, benchmarking, monitoring)Guide production deployment and integration with cloud-native, microservices platformsAdvise stakeholders, shape governance and standards, promote Azure adoption, and mentor teams on responsible AI and best practicesFull timePosting Date: 2026-06-01