info_outline
X Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
New York, NY, USA; Austin, TX, USA; Chicago, IL, USA; Addison, TX, USA; Detroit, MI, USA; Houston, TX, USA.
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 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 architecting AI systems on cloud platforms (e.g. Google Cloud Platform (GCP)).
- Experience leading technical discovery sessions with customers.
Preferred qualifications: - Master's degree 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 Large Language Model (LLM) native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
About the jobAs a Generative AI (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 will 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 issues that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you will 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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
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 Return on Investment (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.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy .
