Senior Forward Deployed Engineer, GenAI, YouTube GTM Operations

Job description

Build and iterate on GenAI proof-of-concepts (Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic Frameworks) to demonstrate feasibility, translating business problems into software. Lead delivery of complex, production-grade AI solutions (e.g., multi-agent systems, model context protocol servers) from rapid prototypes to maximize business Return on Investment (ROI). Partner with Product Managers and stakeholders to co-create tool roadmaps that enable YouTube's business operations. Author technical designs, write clean code, build intuitive frontends, define metrics, and execute deployment. Build high-performance eval pipelines and observability frameworks to ensure agentic systems meet accuracy, safety, and latency requirements. Resolve technical hurdles preventing AI maturity, including data readiness gaps, system integration complexities, edge cases, and state-management challenges. Minimum Qualifications: Bachelor's degree in Computer Science, Electrical Engineering, Mathematics or related quantitative field, or equivalent practical experience in software development. 6 years of experience in full-stack software development and system design. Experience with front-end languages (e.g., JavaScript or TypeScript). Experience with back-end languages (e.g., Java, Python, Go or C++) and building applied AI solutions/agentic workflows around pre-trained models. Experience working with database technologies (e.g., SQL, NoSQL), distributed systems, and designing back-end data pipelines. Preferred Qualifications: 2 years of experience as a Technical Lead or Engineering Manager, including zero-to-one delivery and scoping in ambiguous environments. 2 years of experience with Site Reliability Engineering, Information Security, or Developer Operation practices, with practical enterprise AI experience (LLM evals, observability, safety). Experience building advanced GenAI (multi-step LLM, multi-agent systems, or MCP integrated with orchestration frameworks). Experience with AI data infrastructure: vector databases, embedding generation, search architectures, and state-management challenges. Experience integrating tools with enterprise business systems and CRMs. Knowledge of GTM/sales workflows.