Google Cloud is expanding its enterprise artificial intelligence team in Germany. The Senior Forward Deployed Engineer, Generative AI position is a hands-on technical role focused on taking enterprise LLM applications from proof-of-concept to production infrastructure.
Available across key tech hubs including Munich, Berlin, Frankfurt, and Hamburg, this role bridges advanced foundational models like Google Gemini and Vertex AI with real-world enterprise architectures.
Role Summary & Compensation
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Position Title: Senior Forward Deployed Engineer — Generative AI
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Organization: Google Cloud Engineering
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Locations: Munich, Berlin, Frankfurt, or Hamburg (Germany)
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Employment Type: Full-time
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Base Salary Range: €128,000 – €131,000 / year
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Total Compensation Package: Base salary + 15% target bonus + Google equity (GSUs) + standard Germany enterprise benefits package
What a Forward Deployed AI Engineer Does at Google Cloud
Unlike traditional sales engineering or high-level architecture roles, a Forward Deployed Engineer (FDE) operates directly within customer development environments. You will write code, build data pipelines, and design resilient backends alongside customer engineering teams.
Your primary focus is solving the technical friction points that emerge when scaling generative models inside complex, highly regulated enterprise stacks (such as banking, automotive, and manufacturing).
Core Responsibilities
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Building Enterprise RAG & Vector Systems
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Design, implement, and optimize Retrieval-Augmented Generation (RAG) pipelines for large-scale unstructured datasets.
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Integrate high-throughput vector databases with existing enterprise data lakes and data warehouses.
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Deploying Agentic AI Workflows
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Transition complex agentic workflows into stable production environments.
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Implement automated fallback mechanisms, error handling, and state-management patterns for multi-step reasoning systems.
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Observability, Tracing & Evaluation Harnesses
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Establish custom evaluation pipelines to quantify model accuracy, hallucination rates, and task completion metrics.
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Integrate distributed tracing and monitoring to track end-to-end latency, token consumption, and cost per request.
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Technical Architecture & Discovery
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Lead deep technical discovery sessions with customer architects to audit data flow, security boundaries, and API limits before execution.
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Translate unstructured enterprise challenges into scalable cloud design patterns using GCP tools.
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Platform Feedback & Engineering Standards
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Identify recurring product gaps across customer deployments and collaborate directly with core Vertex AI and Gemini engineering teams to refine the underlying Google Cloud platform.
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Mentor customer developers on production-grade Python patterns, CI/CD for AI applications, and robust testing protocols.
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Candidate Qualifications
Required Experience
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Education or Background: Bachelor’s degree in Computer Science, Software Engineering, or a related quantitative field (or equivalent practical engineering experience).
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Software Engineering: 5+ years of experience developing, testing, and maintaining production-grade software using Python (or languages like Go, Node.js, or C++).
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Cloud & AI Deployment: Proven track record of shipping end-to-end Machine Learning or Generative AI systems into live cloud production environments (GCP, AWS, or Azure).
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Data Engineering: Practical experience structuring data workflows using vector indexing, embeddings, and enterprise search tools.
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Technical Leadership: Ability to lead architectural discussions, conduct code reviews, and drive technical decision-making with external development teams.
Preferred Qualifications
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Advanced Degree: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or Machine Learning.
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Agentic Frameworks: Familiarity with frameworks such as LangGraph, CrewAI, or Google’s Agent Development Kit (ADK), alongside patterns like ReAct, self-reflection, and hierarchical task orchestration.
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LLM Infrastructure Optimization: Understanding of LLM-native performance metrics, including state optimization, caching strategies, dynamic prompt routing, and inference latency reduction.
Why Apply for This Position in Germany?
Germany hosts a significant portion of Google Cloud’s European engineering operations. Joining the team in Munich, Berlin, Frankfurt, or Hamburg places you directly inside core engineering workflows, working on mission-critical AI systems without leaving the EU.
This position is ideal for senior backend engineers, ML engineers, and AI architects who prefer hands-on coding over high-level consulting and want to work directly with Google’s generative AI stack.
How to Apply
To review the full position requirements or submit an application, visit the official page:
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