Senior Forward Deployed Engineer, GenAI, Google Cloud

Responsibilities

• Serve as a developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol [MCP] servers) that drive measurable Return on Investment (ROI).
• Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters as part of an expert team.
• Build evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
• Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
• Be able to co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
• - Serve as a developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol [MCP] servers) that drive measurable Return on Investment (ROI). - Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters as part of an expert team. - Build evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency. - Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams. - Be able to co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.

Minimum qualifications:

Preferred qualifications:

Qualifications

• Minimum qualifications: - Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. - 5 years of experience with software development using Python or similar coding languages. - Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP). - Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions. - Experience managing technical discovery sessions. Preferred qualifications: - Master’s degree or PhD in AI, Computer Science, or a related technical field. - 8 years of experience with software development using Python or similar coding languages. - Experience in customer-facing role, engaging with, and presenting to, technical stakeholders and executive leaders - Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation). - Knowledge of Large Language Model (LLM) native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.