Forward Deployed Engineer, Generative AI, Geo

Google•Mountain View, CA

1d•$152,000 - $221,000

About The Position

The Forward Deployed Engineer (FDE) for Google Maps Platform is a specialized engineering role at the intersection of product development and customer implementation. FDEs embed within the technical ecosystems of complex partners to ensure Google’s geospatial technology solves real-world business problems at scale. The role provides hands-on deployment of complex Geospatial AI systems and turns insights from customer engagements into input for the Google Maps Platform product roadmap. As a Technical Solutions Consultant, the role also involves owning technical relationships with major advertising clients or product partners and leading cross-functional teams in Engineering, Sales, and Product Management. The consultant balances business and partner needs with technical constraints, develops solutions, builds tools and automates products, and oversees technical execution and business operations. The Geo team builds mapping products and services, including Maps, Earth, Street View, and Google Maps Platform, and enables developers to use Google Maps Platform in their apps and websites. Individual pay is determined by job-related skills, experience, and relevant education or training. The listed U.S. pay range is $152,000–$221,000, plus a 15% bonus target, equity, and benefits.

Requirements

Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
At least 5 years of software development experience using Python or similar coding languages.
Experience taking production-grade AI-driven solutions from conception to launch for customers.
Experience managing technical discovery sessions with customers.
Experience building structured and unstructured data pipelines using vector databases and Retrieval-Augmented Generation (RAG)-like architectures for enterprise AI solutions.

Nice To Haves

Master’s degree or PhD in AI, Computer Science, or a related technical field.
Experience implementing multi-agent systems using frameworks such as LangGraph, CrewAI, or ADK and patterns such as ReAct, self-reflection, or hierarchical delegation.
Knowledge of LLM-native metrics, such as tokens per second and cost per request, and techniques for optimizing state management and granular tracing.

Responsibilities

Serve as a developer for complex AI applications, moving rapid prototypes into production-grade agentic workflows, such as multi-agent systems and Model Context Protocol (MCP) servers, that deliver measurable return on investment.
Architect and code integrations between Google AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters, as part of an expert team.
Build high-performance 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 engineering teams.
Co-build with customer engineering teams to establish Google-grade development best practices and support long-term project success and high end-user adoption.
Lead cross-functional teams in Engineering, Sales, and Product Management to apply emerging technologies for external clients and partners.
Oversee technical execution and business operations, and support solution design, testing, data analysis, and partner support.
Develop tools, automate products, and contribute to product strategy and project and resource prioritization.
Provide hands-on deployment of complex Geospatial AI systems for partners and relay field insights to the Google Maps Platform product roadmap.