Staff Forward Deployed Engineer, GenAI, Google Cloud
- Location
- Onsite (Warsaw, Masovian Voivodeship)
- Compensation
- PLN 480k - PLN 492k/yr
- Employment
- Full-time
- Level
- Senior Level
Posted 2 days ago
About the Role
Join Google Cloud’s Go-To-Market team as a Forward Deployed Engineer to build and deploy production-grade agentic AI solutions directly within customer environments. You will bridge the gap between Google's frontier AI products and customer infrastructure, serving as both a builder and technical consultant.
Skills
Python
TypeScript
Google Cloud Platform
GenAI
RAG
Vector Databases
Multi-agent Systems
LangGraph
CrewAI
Vertex AI
Gemini
API Development
System Architecture
Data Pipelines
Observability
Technical Mentorship
Benefits
- Health benefits
Perks
- Bonus target
- Equity
Full job details
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 8 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, TypeScript or comparable languages.
- Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI and hardware infrastructure requirements.
- Experience designing and building AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
- Experience building pipelines for structured, unstructured data, incorporating vector databases and Retrieval-Augmented Generation (RAG)-like architectures to power enterprise-grade AI solutions.
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 Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation.
- Knowledge of large language model native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
About the job:
As a GenAI Forward Deployed Engineer at Google Cloud, you will be an embedded builder bridging the gap between frontier AI products and production-grade reality for our customers. You will function as a builder-consultant, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.In this role, you will manage 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 accounts, you will serve a dual purpose: providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.
It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll leverage Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. Poland: zł480000 - zł492000 (PLN) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities:
- Serve as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol servers) that drive measurable return on investment.
- Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.
- 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 technical friction points in Google’s AI stack, converting them into reusable modules or product feature requests for engineering teams.
- Drive engineering excellence by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities.