Forward Deployed Engineer, Google Cloud Consulting

Salary: 160.000 - 200.000 € per year

Requirements:

Bachelors degree or equivalent practical experience.

2 years of experience in designing, building, and deploying NLP models and Generative AI agents.

Experience implementing DevOps and MLOps pipelines.

Experience in building generative AI solutions in a customer-facing role.

Experience in ML infrastructure (e.g., model deployment, model evaluation, data processing, and debugging) and coding in Python.

Ability to communicate in German fluently to support client relationship management in this region.

Masters or PhD in AI, Computer Science, or a related technical field.

Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Googles ADK) and complex patterns like ReAct, self-reflection, and hierarchical delegation.

Knowledge of Large Language Model (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.

Ability to communicate in French, Spanish, Italian or other European languages fluently to support client relationship management in this region.

Responsibilities:

Serve as the primary developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that generate measurable Return on Investment (ROI).

Architect and code the connective tissue between Googles 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 precise requirements for accuracy, safety, and latency.

Identify repeatable field patterns and technical friction points in Googles AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.

Technologies:

AI

AI Agents

Architect

DevOps

Support

LLM

MCP

MLOps

OAuth

Python

React

Security

More:

We are a team working with Googles AI products and customer infrastructure, building production-grade agentic workflows, multi-agent systems, and Model Context Protocol (MCP) servers that deliver measurable ROI. We focus on connecting AI solutions with live APIs, legacy data silos, and security perimeters, while building evaluation pipelines and observability frameworks to ensure accuracy, safety, and latency requirements are met. We also identify reusable patterns and product friction points to help shape engineering improvements.

last updated 38 week of 2026