Why This Role Stands Out
This Gen AI Engineer role offers an exciting opportunity to build cutting-edge AI solutions directly within customer environments, pushing the boundaries of what's possible with AI. You'll thrive here if you're a highly motivated engineer with a founder's mindset, eager to solve complex integration challenges and directly impact the future of Google Cloud's AI products. Embrace this chance to grow your skills and make a significant impact with a hybrid work model.
Quick Overview
Job Description
Job Title: Gen AI Developer
Location: San Jose, CA - Locals Only
Visa: H1B, for W2
Job Description:
As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you are an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you function as an "innovator-builder," moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment. This role is designed for high-agency engineers with a founder’s mindset. You will address blockers to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you serve a dual purpose: providing "white glove" deployment of complex AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.
Job Responsibilities:
Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
Architect and code the "connective tissue" between Google’s AI products and customer's 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 rigorous 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.
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:
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 architecting AI systems on cloud platforms (e.g., Google Cloud Platform).
Experience building pipelines for structured and unstructured data using both 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 leading technical discovery sessions with customers.
- The key project experience and skill needed is conversational AI experience using Gemini customer experience (GECX)- CCAI, DialogFlow etc and Google Cloud Platform)
Preferred Qualifications:
Master’s or PhD in AI, Computer Science, or a related technical field.
Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing
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