Forward Deployed Engineer, Generative AI, Google Cloud

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

As an AI Forward Deployed Engineer (FDE) at Google Cloud Consulting, you will be an embedded builder who bridges the gap between frontier AI products and reality within accounts. Unlike traditional advisory roles, you will function as a "builder-consultant," moving beyond high-level architecture to provide "white glove" deployment for enterprise-grade maturity.

This role is designed for high-agency engineers with a founder’s mindset who address the technical hurdles that prevent complex AI from achieving wide-scale business impact.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Poland: zł280000 - zł287000 (PLN) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Serve as the lead 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 customers' live infrastructure, including APIs, legacy data silos, and security perimeters.
• Build high-performance evaluation (Eval) pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.
• Identify repeatable field patterns and technical "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.

Qualifications

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 2 years of experience with software development programming in Python, or 1 year of experience with an advanced degree.
• 2 years of experience with Generative AI techniques (e.g., LLMs, Multi-Modal, and Large Vision Models) or with Generative AI-related concepts (language modeling and computer vision).
• Experience implementing DevOps and MLOps pipelines.

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, or Google’s ADK) and complex patterns like ReAct, self-reflection, and hierarchical delegation.
• Knowledge of "LLM-native" metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
• Proven ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.