Principal Software AI Engineer (R-20013)

About the role

Responsibilities

• Define the architecture and technical direction for enterprise AI/ML and GenAI capabilities, including agentic and conversational AI solutions using platforms and models such as Vertex AI Agent Builder/ADK and Gemini
• Lead the design and delivery of production-grade LLM applications, including embeddings, RAG pipelines, vector database integration, tool use, orchestration, and multi-agent patterns
• Establish reusable AI engineering standards, reference architectures, design patterns, and governance controls for secure, responsible, observable, and maintainable AI solutions
• Provide technical leadership for end-to-end MLOps and CI/CD capabilities supporting model experimentation, evaluation, validation, deployment, monitoring, and lifecycle management
• Architect and guide scalable cloud-native AI services on GCP and Kubernetes using Docker, Infrastructure as Code such as Terraform, and event-driven integration patterns
• Lead the design of data pipelines, APIs, and enterprise integrations that embed AI/ML capabilities into business applications and collaboration platforms
• Define model and system evaluation approaches for quality, safety, latency, reliability, cost, and business effectiveness; guide production monitoring, incident response, root-cause analysis, and prevention
• Partner with Product Owners, Data Scientists, AI Data Engineers, Platform Architects, Security, Risk and Compliance, and application teams to evaluate trade-offs and deliver cost-effective solutions aligned to enterprise standards
• Lead technical design reviews, proofs of concept, and technology evaluations; influence build-versus-buy decisions and the adoption of emerging AI tools and platforms
• Provide training, guidance, and mentorship to engineers and raise engineering capability through code reviews, architecture reviews, knowledge sharing, and best-practice adoption
• Additional duties as assigned