Forward Deployed Engineer IV, Applied AI, Google Cloud

About the role

This opportunity will remain online based on business needs which may be before or after the specified date.

Responsibilities

• Serve as the lead developer for conversational AI and customer experience 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.
• Architect and code conversational flows that are functional, and optimized for the connective tissue between Google’s conversational AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
• Build high-performance evaluation pipelines and observability frameworks to optimize agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
• Identify repeatable field patterns and technical friction points in Google’s Applied Artificial Intelligence (AAI) stack, converting them into reusable modules or product feature requests for Engineering teams.
• Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption.

Requirements

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 8 years of experience with software development using Python or similar coding languages.
• Experience deploying resources via Terraform or similar tools to automate the setup of agents, functions, or networking.
• Experience building full-stack applications that interact with enterprise IT infrastructures and developing external customer projects.
• Experience architecting AI systems on cloud platforms (e.g., Google Clloud Platform (GCP)).

Preferred qualifications

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
• Experience debugging agent logic and optimizing tool selection, including tracing conversation identifications (IDs) across microservices to identify and resolve failures in real-time.
• Experience connecting agents to enterprise knowledge bases and optimizing retrieval-augmented Generation (RAG) chunking to prevent hallucinations.
• Track record of troubleshooting live, high-traffic systems during critical windows.
• Ability to travel up to 50% of the time.

Qualifications

• Minimum qualifications: Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 8 years of experience with software development using Python or similar coding languages.
• Experience deploying resources via Terraform or similar tools to automate the setup of agents, functions, or networking.
• Experience building full-stack applications that interact with enterprise IT infrastructures and developing external customer projects.
• Experience architecting AI systems on cloud platforms (e.g., Google Clloud Platform (GCP)).

Skills

• Software engineering skills.
• Machine Learning operations expertise.
• Cloud infrastructure knowledge.

Benefits

• Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
• US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits