Build GenAI PoCs (LLMs, RAG, agentic frameworks) to demonstrate feasibility to stakeholders, translating ambiguous business problems into software solutions. Serve as engineering Lead delivering complex AI applications, transitioning rapid prototypes to production-grade systems (e.g., multi-agent systems, MCP servers) that drive Return on Investment (ROI). Act as a trusted engineering partner to product managements and stakeholders, co-creating tool roadmaps that enable YouTube's business operations.
Author technical designs, write clean/maintainable code, build front-ends, and deliver from scoping to deployment. Build high-performance eval pipelines and observability frameworks to resolve AI bottlenecks (data readiness, system integration, state-management) while ensuring accuracy, safety, compliance, and latency.
Job description provided by Google.
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