Forward Deployed Engineer IV, Generative AI, Google Cloud

Google•Pittsburgh, PA

1d•$207,000 - $300,000

About The Position

As a Generative AI Forward Deployed Engineer at Google Cloud, you will embed with customers to turn frontier AI products into production-grade solutions. You will move beyond high-level architecture to code, debug, and jointly deliver custom agentic solutions within customer environments. The role focuses on addressing integration complexity, data readiness, and state-management challenges that prevent AI systems from reaching enterprise-grade maturity. You will provide deployment support for complex AI systems and relay field insights to inform Google Cloud’s product roadmap. You will work with Google Cloud’s Go-To-Market team and its AI portfolio, including Gemini models and the Vertex AI platform, collaborating with Customer Engineering teams and drawing on access to DeepMind engineering and research expertise. The listed US compensation is $207,000–$300,000, plus a 20% bonus target, equity, and benefits. Individual pay depends on job-related skills, experience, and relevant education or training.

Requirements

Bachelor’s degree in Engineering, Computer Science, or a related field, or equivalent practical experience.
8 years of experience with software development using Python or similar coding languages.
Experience building pipelines for structured and unstructured data using vector databases and RAG-like architectures to power enterprise AI solutions.
Experience taking production-grade AI-driven solutions from conception to launch for customers.
Experience architecting AI systems on cloud platforms, such as Google Cloud Platform.
Experience leading technical discovery sessions with customers.

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 complex 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

Develop complex AI applications, taking rapid prototypes to production-grade agentic workflows, including multi-agent systems and MCP servers, that deliver measurable ROI.
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 and turn them into reusable modules or formal product feature requests for Engineering teams.
Co-build with Customer Engineering teams to establish Google-grade development practices and support long-term project success and end-user adoption.
Lead technical discovery sessions with customers.