Senior Forward Deployed Engineer, GenAI, YouTube

Minimum qualifications:

• Bachelor's degree in Computer Science, Electrical Engineering, Math or a related quantitative field, or equivalent practical experience.
• 6 years of experience in full-stack software development and system design.
• Experience with back-end langu,ges (e.g., Java, Python, or C++).
• Experience with front-end languages (e.g., JavaScript or TypeScript).
• Experience working with database technologies (e.g., SQL, NoSQL).
• Experience building AI-powered products, featuring technologies such as long context windows, Retrieval Augmented Generation (RAG), etc.

Preferred qualifications:

• 2 years of experience as a tech lead or engineering manager, including taking ownership of zero-to-one product delivery.
• 2 years of experience with Site Reliability Engineering, Information Security, or DevOps practices, paired with practical experience in enterprise AI solutions.
• Experience building advanced GenAI architectures, including multi-step Large Language Model (LLM) applications, multi-agent systems, or integrating the MCP with modern orchestration frameworks.
• Experience with AI data infrastructure, including vector databases, embedding generation, search architectures, and state-management challenges for AI systems.
• Experience with Go-To-Market operations and enterprise sales workflows, or experience building tools that integrate with enterprise business systems.

About the job

Responsibilities

• Lead the delivery of complex AI applications, transitioning from rapid prototypes to production-grade, AI-powered solutions (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive measurable return on investment.
• Prototype rapid proof-of-concepts (PoCs) using frontier GenAI (e.g., LLMs, RAG, agentic frameworks) to demonstrate technical feasibility to stakeholders, translating ambiguous business problems into tangible software solutions.
• Ship enterprise-grade solutions by owning the full software development lifecycle, authoring technical design documents, writing clean code, building front-end, and executing delivery.
• Engineer high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
• Solve enterprise AI blockers by systematically identifying and resolving technical issues including data readiness gaps, system integration complexities, and agentic state-management challenges.