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Job Description
Why GM Financial 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:
The Principal AI Engineer is a hands‑on technical leader and thought partner who guides teams in designing, building, and delivering enterprise‑grade Generative AI solutions, including agentic systems, multi‑agent orchestration, and Retrieval‑Augmented Generation architectures. This role partners closely with product, enterprise architecture, security, and engineering leadership to ensure AI capabilities are scalable, reliable, compliant, and aligned with organizational standards. Success requires strong technical judgment, the ability to mentor and grow engineering talent, and a commitment to advancing responsible AI adoption across the enterprise. In this role, you will: Guide and grow an AI engineering team by fostering technical excellence, accountability, continuous learning, and strong architectural decision‑making; support hiring, onboarding, and skills development. Design, build, and deliver production‑ready Generative AI solutions, including agentic and multi‑agent systems, RAG pipelines, orchestration frameworks, APIs, microservices, automated pipelines, and testing, with hands‑on contribution in Python, C#, or Java as needed. Define and standardize AI architecture, patterns, libraries, and development practices, selecting and applying cloud AI solutions aligned with enterprise technology strategy. Ensure AI solutions are secure, compliant, and responsible by embedding privacy, data governance, auditability, PII protection, risk mitigation, and model evaluation in collaboration with security, legal, compliance, and data governance teams. Partner with product, architecture, and engineering stakeholders to drive aligned solution direction, predictable delivery, and organization‑wide adoption of AI best practices. Drive innovation and thought leadership through continuous exploration of emerging Generative AI technologies, experimentation, proof‑of‑concepts, and internal knowledge sharing.
