Technical Principal - Gen AI Architect

Why GMF Technology?

Innovation 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.

About The Role:  

We are seeking a Principal Software Engineer with deep expertise in Generative AI to lead the design and architecture of next-generation AI applications. This is a hands-on, architecture-driven role for a seasoned technologist who thrives in regulated environments and is passionate about building secure, scalable, and intelligent systems.

You will be responsible for working with cross functional teams to implement AI solutions using agentic patterns, multi-agent frameworks, Retrieval-Augmented Generation (RAG) architectures or SaaS solutions. You’ll also play a key role in evangelizing best AI architectural best practices and driving innovation across the organization. 

• Architect and build production-grade Generative AI applications using modern agentic and multi-agent design patterns.
• Collaborate with cross functional teams to set architecture standards & guidelines for AI implementations in conjunction with existing enterprise architecture standards
• Design and implement reusable working AI patterns for enterprise use
• Ensure AI systems meet privacy, governance, and compliance standards, especially in highly regulated industries such as finance.
• Evaluate and select appropriate GenAI platforms (e.g., Azure AI Foundry, Databricks Mosaic AI) based on project needs.
• Lead architectural reviews and influence enterprise-wide technology decisions.
• Mentor engineers and promote a culture of innovation, quality, and accountability.
• Stay current with emerging AI technologies, evaluation frameworks, and industry trends.