Partner Forward Deployed Engineer, Google Cloud (French, German)

Requirements

• 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, and architecting AI systems on cloud platforms (e.g., Google Cloud Platform).
• Experience leading technical discovery sessions with customers.
• Ability to communicate in French or German fluently as this is a customer-facing role that requires interactions in French or German with local stakeholders.

Nice to Haves

• 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).
• Experience in a post-sales or technical consulting delivery function.
• Knowledge of Large Language Model (LLM) native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
• Strong communication skills, and proven experience enabling technical teams on Agentic AI, at scale.

What You'll Be Doing

• 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 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 pre-sales and product teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.

Perks and Benefits

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